COLOR CORRECTION MATRIX OPTIMIZATION METHOD, ELECTRONIC DEVICE, AND MEDIUM

§102 §103

DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Preliminary Amendment The Preliminary Amendment submitted on 01/29/2025 has been entered and made of record. Status of Claims This communication is in response to the Application Filed on 01/29/2025. Claims 1-7 and 9-21 are pending in this application. Claim 8 is canceled and claims 11-21 are newly added in the preliminary amendment filed on 1/29/2025. Information Disclosure Statement The information disclosure statements (IDS) submitted on 01/29/2025 and 06/30/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Claim Objections Claim 6 is objected to because of the following informalities: Claim 6 recites “the hue rotation matrix” on line 5 and “the saturation scaling matrix” on line 6. This may create an antecedent basis issue under 35 U.S.C § 112. To eliminate any ambiguity, perhaps “the hue rotation matrix” ought to be “a hue rotation matrix” and “the saturation scaling matrix” ought to be “a saturation scaling matrix”. Appropriate correction is required. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1, 2, 9-11, and 17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wu et al. (CN 112073703 A, hereinafter, “Wu”, or "Wu Translation" corresponding to the translated document, or "Wu Original" corresponding to the original document). Regarding claim 1, Wu discloses a color correction matrix optimization method (See Wu Translation, ¶ [0037] Fig. 1, a color correction matrix adjustment method), comprising: performing correction processing on a color source matrix of an acquired color chart image (See Wu Translation, ¶ [0051] You can directly capture the uncorrected image to obtain the color chart image, and then use the steps in S102-S104 to obtain the correction matrix. Examiner considers the uncorrected image (considered to be the color chart matrix) to be used for a correction process (considered to be steps S102-S104) to get a correction matrix (considered to be a target or original correction matrix that needs optimizing)) based on a color correction matrix (See Wu Translation, ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix. Examiner considers the matrix ‘a’ to be the color correction matrix) to obtain an output color matrix (See Wu Translation, ¶ [0072] Specifically, the RGB values of each deviation color block in the RGB format color chart image can be obtained, and then the first matrix can be built based on the RGB values. Examiner considers the first matrix as the output color matrix); determining a global hue error (See Wu Translation, ¶ [0061] calculate the color error value between each color block and the standard color block based on the color value. Examiner considers the color error value to be the global hue error, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0058] PNG media_image1.png 80 374 media_image1.png Greyscale . ∆ (i.e., ‘Delta’) C is considered to be the color error value) and a saturation constraint regularization term (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers the saturation error to be the saturation constraint regularization value, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0062] PNG media_image2.png 89 547 media_image2.png Greyscale . ∆ (i.e., ‘Delta’) E is considered to be the saturation error value) based on Lab coordinates of the output color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the color block, which is considered to be the output color matrix) and Lab coordinates of a target color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the standard color block, which is considered to be the target color matrix) of a target color chart image (See Wu Translation, ¶ [0076] Specifically, each deviation color patch corresponds to a standard color patch, and a second matrix is established using the RGB values of the corresponding standard color patch. Examiner considers the second matrix to be a target color chart image/matrix) and constructing a loss function based on the global hue error and the saturation constraint regularization term (See Wu Translation, ¶ [0085] Specifically, the total error between each deviation color patch adjusted using matrix a and the standard color patch can be calculated. This total error can be a loss value; ¶ [0087] Where n is the number of deviation color patches, ΔC_i is the color error value of the i-th deviation color patch, ΔE_i is the saturation error value of the color patch, i is a positive integer less than or equal to n, Tc is the first threshold, Te is the second threshold, and Δf is the loss value; See Wu Original, ¶ [0081] PNG media_image3.png 85 700 media_image3.png Greyscale . ∆ (i.e., ‘Delta’) f is considered to be the loss function), wherein the Lab coordinates are coordinates in a Lab color space (See Wu Translation, ¶ [0060] The Lab color model consists of three elements: lightness (L), a, and b, which are two color Channels. Examiner considers it to be obvious to one skilled in the art to know that the lab color model is a 3D model with 3D coordinates (L, a*, b*)); and updating the color correction matrix based on a value of the loss function until the value of the loss function converges to obtain an optimal color correction matrix (See Wu Translation, ¶ [0085] However, the above formula can yield multiple matrices 'a', which need to be filtered; ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix; ¶ [0091] The original color correction matrix b is corrected by matrix a to obtain the target color correction matrix c. Examiner considers the selection of matrix a and correcting matrix b with matrix a as updating the color correction matrix. Multiple matrix a are generated and thus it is a repetitive process until the matrix a that minimizes the loss value is selected) so that color correction is performed on a to-be-processed image acquired by an image acquisition device by using the optimal color correction matrix (See Wu Translation, ¶ [0091] Since the standard color patch was referenced in the process of obtaining the correction matrix a, the target color correction matrix c is used to correct the image. Examiner considers the image as the to-be-processed image). Regarding claim 2, in which claim 1 is incorporated, Wu discloses wherein determining a global hue error (See Wu Translation, ¶ [0061] calculate the color error value between each color block and the standard color block based on the color value. Examiner considers the color error value to be the global hue error, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0058] PNG media_image1.png 80 374 media_image1.png Greyscale . ∆C is considered to be the color error value) and a saturation constraint regularization term (See Wu Translation, ¶ ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers the saturation error to be the saturation constraint regularization value, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0062] PNG media_image2.png 89 547 media_image2.png Greyscale . ∆E is considered to be the saturation error value) based on Lab coordinates of the output color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the color block, which is considered to be the output color matrix) and Lab coordinates of a target color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the standard color block, which is considered to be the target color matrix) of a target color chart image (See Wu Translation, ¶ [0076] Specifically, each deviation color patch corresponds to a standard color patch, and a second matrix is established using the RGB values of the corresponding standard color patch. Examiner considers the second matrix to be a target color chart image/matrix) and constructing a loss function based on the global hue error and the saturation constraint regularization term (See Wu Translation, ¶ [0085] Specifically, the total error between each deviation color patch adjusted using matrix a and the standard color patch can be calculated. This total error can be a loss value; ¶ [0087] Where n is the number of deviation color patches, ΔC_i is the color error value of the i-th deviation color patch, ΔE_i is the saturation error value of the color patch, i is a positive integer less than or equal to n, Tc is the first threshold, Te is the second threshold, and Δf is the loss value; See Wu Original, ¶ [0081] PNG media_image3.png 85 700 media_image3.png Greyscale . ∆f is considered to be the loss function) comprises: determining chromaticity coordinates (See Wu Translation, ¶ [0080] Specifically, 'a' can be used to represent the correction matrix; See Wu Original, ¶ [0078], PNG media_image4.png 155 685 media_image4.png Greyscale . Examiner considers there to exist a relationship between the first matrix (first color patch) and second matrix (second color patch). Coordinate pairs are determined based on matrix multiplication rules (R1, R*1)) corresponding to each color patch among a plurality of color patches represented by a plurality of columns of elements in the output color matrix (See Wu Translation, ¶ [0072] Specifically, the RGB values of each deviation color block in the RGB format color chart image can be obtained, and then the first matrix can be built based on the RGB values. The first matrix can be as follows; See Wu Original, ¶ [0068], PNG media_image5.png 394 556 media_image5.png Greyscale . Examiner considers this first matrix with R, G, and B values as the output color matrix) and a plurality of columns of elements in the target color matrix (See Wu Translation, ¶ [0076] Specifically, each deviation color patch corresponds to a standard color patch, and a second matrix is established using the RGB values of the corresponding standard color patch. The second matrix can be; See Wu Original, ¶ [0072] PNG media_image6.png 362 541 media_image6.png Greyscale . Examiner considers this second matrix with R*, G*, and B* values as the target color matrix), wherein the chromaticity coordinates are coordinates of the output color matrix and the target color matrix in a chromaticity plane after the output color matrix and the target color matrix are transformed into the Lab color space (See Wu Translation, ¶ [0059] S202, Convert the color chart image into Lab format; ¶ [0099] The format conversion submodule is used to convert the color chart image into Lab format, wherein the Lab format color chart image includes brightness values and color values. Examiner considers the conversion to lab format, which takes place at the beginning of the process, to give color values in L, a*, b* format thus the coordinate pairs are also in this new format); determining the global hue error (See Wu Translation, ¶ [0061] calculate the color error value between each color block and the standard color block based on the color value) and the saturation constraint regularization term (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block) based on the chromaticity coordinates corresponding to each color patch, (See Wu Translation, ¶ [0064] Where a is the first color value of the color block in the color chart image within a preset first range, b is the second color value of the color block in the color chart image within a preset second range, a*is the third color value of the standard color block within the first range, b* is the fourth color value of the standard color block within the second range; ¶ [0068] Where L is the brightness value of the color block in the color chart image, a is the first color value of the color block in the color chart image within a preset first range, b is the second color value of the color block in the color chart image within a preset second range, L* is the brightness value of the standard color block, a*is the third color value of the standard color block within the first range, b* is the fourth color value of the standard color block within the second range); and constructing the loss function based on a sum of the saturation constraint regularization term and the global hue error (See Wu Original, ¶ [0081], PNG media_image3.png 85 700 media_image3.png Greyscale . Examiner considers the loss function to use summation of ∆E, hue error, and ∆C, saturation error). Regarding claim 9, Wu discloses an electronic device (See Wu Translation, ¶ [0110] the terminal device4) comprising: at least one processor (See Wu Translation, ¶ [0110] at least one processor 40); and a memory communicatively connected to the at least one processor (See Wu Translation, ¶ [0110] a memory 41; See Wu Original, Fig. 4. Examiner considers the memory 41 and processor 40 to be connected as show in Fig. 4 below for clarity), PNG media_image7.png 476 783 media_image7.png Greyscale wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the following (See Wu Translation, ¶ [0110] a computer program 42 stored in the memory 41 and executable on the at least one processor 40; ¶ [0110] When the processor 40 executes the computer program 42, it implements the steps in any of the above method embodiments): performing correction processing on a color source matrix of an acquired color chart image (See Wu Translation, ¶ [0051] You can directly capture the uncorrected image to obtain the color chart image, and then use the steps in S102-S104 to obtain the correction matrix. Examiner considers the uncorrected image (considered to be the color chart matrix) to be used for a correction process (considered to be steps S102-S104) to get a correction matrix (considered to be a target or original correction matrix that needs optimizing)) based on a color correction matrix (See Wu Translation, ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix. Examiner considers the matrix ‘a’ to be the color correction matrix) to obtain an output color matrix (See Wu Translation, ¶ [0072] Specifically, the RGB values of each deviation color block in the RGB format color chart image can be obtained, and then the first matrix can be built based on the RGB values). Examiner considers the first matrix as the output color matrix); determining a global hue error (See Wu Translation, ¶ [0061] calculate the color error value between each color block and the standard color block based on the color value. Examiner considers the color error value to be the global hue error, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0058] PNG media_image1.png 80 374 media_image1.png Greyscale . ∆C is considered to be the color error value) and a saturation constraint regularization term (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers the saturation error to be the saturation constraint regularization value, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0062] PNG media_image2.png 89 547 media_image2.png Greyscale . ∆E is considered to be the saturation error value) based on Lab coordinates of the output color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the color block, which is considered to be the output color matrix) and Lab coordinates of a target color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the standard color block, which is considered to be the target color matrix) of a target color chart image (See Wu Translation, ¶ [0076] Specifically, each deviation color patch corresponds to a standard color patch, and a second matrix is established using the RGB values of the corresponding standard color patch. Examiner considers the second matrix to be a target color chart image/matrix) and constructing a loss function based on the global hue error and the saturation constraint regularization term (See Wu Translation, ¶ [0085] Specifically, the total error between each deviation color patch adjusted using matrix a and the standard color patch can be calculated. This total error can be a loss value; ¶ [0087] Where n is the number of deviation color patches, ΔC_i is the color error value of the i-th deviation color patch, ΔE_i is the saturation error value of the color patch, i is a positive integer less than or equal to n, Tc is the first threshold, Te is the second threshold, and Δf is the loss value; See Wu Original, ¶ [0081] PNG media_image3.png 85 700 media_image3.png Greyscale . ∆f is considered to be the loss function), wherein the Lab coordinates are coordinates in a Lab color space (See Wu Translation, ¶ [0060] The Lab color model consists of three elements: lightness (L), a, and b, which are two color Channels. Examiner considers it to be obvious to one skilled in the art to know that the lab color model is a 3D model with 3D coordinates (L, a*, b*)); and updating the color correction matrix based on a value of the loss function until the value of the loss function converges to obtain an optimal color correction matrix (See Wu Translation, ¶ [0085] However, the above formula can yield multiple matrices 'a', which need to be filtered; ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix; ¶ [0091] The original color correction matrix b is corrected by matrix a to obtain the target color correction matrix c. Examiner considers the selection of matrix a and correcting matrix b with matrix a as updating the color correction matrix. Multiple matrix a are generated and thus it is a repetitive process until the matrix a that minimizes the loss value is selected) so that color correction is performed on a to-be-processed image acquired by an image acquisition device by using the optimal color correction matrix (See Wu Translation, ¶ [0091] Since the standard color patch was referenced in the process of obtaining the correction matrix a, the target color correction matrix c is used to correct the image. Examiner considers the image as the to-be-processed image). Regarding claim 10, Wu discloses a non-transitory computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the following (See Wu Translation, ¶ [0110] a computer program 42 stored in the memory 41 and executable on the at least one processor 40; ¶ [0110] When the processor 40 executes the computer program 42, it implements the steps in any of the above method embodiments; ¶ [0118] computer-readable media may not be electrical carrier signals or telecommunication signals): performing correction processing on a color source matrix of an acquired color chart image (See Wu Translation, ¶ [0051] You can directly capture the uncorrected image to obtain the color chart image, and then use the steps in S102-S104 to obtain the correction matrix. Examiner considers the uncorrected image (considered to be the color chart matrix) to be used for a correction process (considered to be steps S102-S104) to get a correction matrix (considered to be a target or original correction matrix that needs optimizing)) based on a color correction matrix (See Wu Translation, ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix. Examiner considers the matrix ‘a’ to be the color correction matrix) to obtain an output color matrix (See Wu Translation, ¶ [0072] Specifically, the RGB values of each deviation color block in the RGB format color chart image can be obtained, and then the first matrix can be built based on the RGB values). Examiner considers the first matrix as the output color matrix); determining a global hue error (See Wu Translation, ¶ [0061] calculate the color error value between each color block and the standard color block based on the color value. Examiner considers the color error value to be the global hue error, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0058] PNG media_image1.png 80 374 media_image1.png Greyscale . ∆C is considered to be the color error value) and a saturation constraint regularization term (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers the saturation error to be the saturation constraint regularization value, the color block as the output color matrix, and the standard color block as the target color chart/matrix; See Wu Original, ¶ [0062] PNG media_image2.png 89 547 media_image2.png Greyscale . ∆E is considered to be the saturation error value) based on Lab coordinates of the output color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the color block, which is considered to be the output color matrix) and Lab coordinates of a target color matrix (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block. Examiner considers both equations to use a* and b* coordinates from the standard color block, which is considered to be the target color matrix) of a target color chart image (See Wu Translation, ¶ [0076] Specifically, each deviation color patch corresponds to a standard color patch, and a second matrix is established using the RGB values of the corresponding standard color patch. Examiner considers the second matrix to be a target color chart image/matrix) and constructing a loss function based on the global hue error and the saturation constraint regularization term (See Wu Translation, ¶ [0085] Specifically, the total error between each deviation color patch adjusted using matrix a and the standard color patch can be calculated. This total error can be a loss value; ¶ [0087] Where n is the number of deviation color patches, ΔC_i is the color error value of the i-th deviation color patch, ΔE_i is the saturation error value of the color patch, i is a positive integer less than or equal to n, Tc is the first threshold, Te is the second threshold, and Δf is the loss value; See Wu Original, ¶ [0081] PNG media_image3.png 85 700 media_image3.png Greyscale . ∆f is considered to be the loss function), wherein the Lab coordinates are coordinates in a Lab color space (See Wu Translation, ¶ [0060] The Lab color model consists of three elements: lightness (L), a, and b, which are two color Channels. Examiner considers it to be obvious to one skilled in the art to know that the lab color model is a 3D model with 3D coordinates (L, a*, b*)); and updating the color correction matrix based on a value of the loss function until the value of the loss function converges to obtain an optimal color correction matrix (See Wu Translation, ¶ [0085] However, the above formula can yield multiple matrices 'a', which need to be filtered; ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix; ¶ [0091] The original color correction matrix b is corrected by matrix a to obtain the target color correction matrix c. Examiner considers the selection of matrix a and correcting matrix b with matrix a as updating the color correction matrix. Multiple matrix a are generated and thus it is a repetitive process until the matrix a that minimizes the loss value is selected) so that color correction is performed on a to-be-processed image acquired by an image acquisition device by using the optimal color correction matrix (See Wu Translation, ¶ [0091] Since the standard color patch was referenced in the process of obtaining the correction matrix a, the target color correction matrix c is used to correct the image. Examiner considers the image as the to-be-processed image). Regarding claim 11 (drawn to a device), claim 11 is rejected the same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to claim 11, and all the other limitations similar to claim 2 are not repeated herein, but incorporated by reference. Regarding claim 17 (drawn to a non-transitory computer-readable storage medium), claim 17 is rejected the same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to claim 17, and all the other limitations similar to claim 2 are not repeated herein, but incorporated by reference. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or non-obviousness. Claims 3, 4, 12, 13, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (CN 112073703 A, hereinafter, “Wu”, or "Wu Translation" corresponding to the translated document, or "Wu Original" corresponding to the original document) in view of Chiba (US 2005/0018226 A1, hereinafter, “Chiba”). Regarding claim 3, in which claim 2 is incorporated, Wu discloses wherein determining the global hue error (See Wu Translation, ¶ [0061] calculate the color error value between each color block and the standard color block based on the color value) based on the chromaticity coordinates corresponding to each color patch (See Wu Translation ¶ [0064] Where a is the first color value of the color block in the color chart image within a preset first range, b is the second color value of the color block in the color chart image within a preset second range, a*is the third color value of the standard color block within the first range, b* is the fourth color value of the standard color block within the second range) comprises: for a color patch pair represented by a same column of elements in the output color matrix and the target color matrix (See Wu Translation, ¶ [0080] Specifically, 'a' can be used to represent the correction matrix; See Wu Original, ¶ [0078], PNG media_image4.png 155 685 media_image4.png Greyscale . Examiner considers there to exist a relationship between the first matrix (R, first color patch) and second matrix (R*, second color patch). Color patch pairs are determined based on matrix multiplication rules which look at the elements in the same column), determining a hue error of the color patch pair (See Wu Translation, ¶ [0061] calculate the color error value between each color block and the standard color block based on the color value) [based on an included angle between chromaticity coordinate vectors of the color patch pair], [wherein each of the chromaticity coordinate vectors is a vector whose start point is an origin and whose end point is the chromaticity coordinates; and] [and calculating the global hue error based on a weighted average value of hue errors of a plurality of color patch pairs.] However, Wu does not explicitly disclose [determining a hue error of the color patch pair] based on an included angle between chromaticity coordinate vectors of the color patch pair, wherein each of the chromaticity coordinate vectors is a vector whose start point is an origin and whose end point is the chromaticity coordinates; and and calculating the global hue error based on a weighted average value of hue errors of a plurality of color patch pairs. Chiba teaches [determining a hue error of the color patch pair] based on an included angle between chromaticity coordinate vectors of the color patch pair (See Chiba, ¶ [0064] In step S128, a hue error .theta.s.sup.2 is obtained in accordance with the L*a*b* signals of the hue optimizing goal colors C.sub.me'(1)-C.sub.me'(18), which were preset in step S112, and the L*a*b* signals of the hue corrected colors C.sub.es'(1)-C.sub.es'(18). Examiner considers it to be obvious to one skilled in the art a point in the chromaticity plane (a, b) in color space has set of coordinates that starts at the origin and the end point being the designated (a, b) points which form a vector. The vector will form an angle in the 3D space as seen below in Fig. 2 for clarity), PNG media_image8.png 495 523 media_image8.png Greyscale wherein each of the chromaticity coordinate vectors is a vector whose start point is an origin and whose end point is the chromaticity coordinates (See Chiba, ¶ [0036] A color that corresponds to an input color C.sub.in and an objective color C.sub.me (hereinafter, referred to as a goal color), to which the input color should be adjusted, are indicated as respective points in this Lab color space. Examiner considers it to be obvious to one skilled in the art a point in the chromaticity plane (a, b) in color space has set of coordinates that starts at the origin and the end point being the designated (a, b) points as seen above in Fig. 2 for clarity); and and calculating the global hue error based on a weighted average value of hue errors of a plurality of color patch pairs (See Chiba, ¶ [0086] sum of the squares of the hue angle differences … the hue angle differences .DELTA..theta. in Eq. (24) may be weighted to improve the coincidence of hue). Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Wu’s reference to [determining a hue error of the color patch pair] based on an included angle between chromaticity coordinate vectors of the color patch pair, wherein each of the chromaticity coordinate vectors is a vector whose start point is an origin and whose end point is the chromaticity coordinates; and calculating the global hue error based on a weighted average value of hue errors of a plurality of color patch pairs based on the method of Chiba’s reference. The suggestion/motivation would have been to detect a difference in hue since a difference in the hue is more easily recognized as a difference in the color, when compared to a difference in saturation, due to the nature of human perception as suggested by Chiba at ¶ [0041] and improve the coincidence of hue as suggested by Chiba at ¶ [0086]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Chiba with Wu to obtain the invention as specified in claim 3. Regarding claim 4, in which claim 2 is incorporated, Wu discloses wherein determining the saturation constraint regularization term (See Wu Translation, ¶ [0065] calculate the saturation error value between each color block and the standard color Block) based on the chromaticity coordinates corresponding to each color patch (See Wu Translation, ¶ [0068] Where L is the brightness value of the color block in the color chart image, a is the first color value of the color block in the color chart image within a preset first range, b is the second color value of the color block in the color chart image within a preset second range, L* is the brightness value of the standard color block, a*is the third color value of the standard color block within the first range, b* is the fourth color value of the standard color block within the second range) comprises: [determining an average value of first distances between an origin and] chromaticity coordinates of a plurality of color patches represented by the plurality of columns of elements in the output color matrix (See Wu Translation, ¶ [0099] The format conversion submodule is used to convert the color chart image into Lab format, wherein the Lab format color chart image includes brightness values and color values; ¶ [0068] Where L is the brightness value of the color block in the color chart image, a is the first color value of the color block in the color chart image within a preset first range, b is the second color value of the color block in the color chart image within a preset second range, L* is the brightness value of the standard color block, a*is the third color value of the standard color block within the first range, b* is the fourth color value of the standard color block within the second range. Examiner considers all elements in the multiple columns of the first matrix (output color matrix) to have been converted to color space with chromaticity coordinates (a*, b*)) and [determining an average value of second distances between the origin and] chromaticity coordinates of a plurality of color patches represented by the plurality of columns of elements in the target color matrix (See Wu Translation, ¶ [0099] The format conversion submodule is used to convert the color chart image into Lab format, wherein the Lab format color chart image includes brightness values and color values; ¶ [0068] Where L is the brightness value of the color block in the color chart image, a is the first color value of the color block in the color chart image within a preset first range, b is the second color value of the color block in the color chart image within a preset second range, L* is the brightness value of the standard color block, a*is the third color value of the standard color block within the first range, b* is the fourth color value of the standard color block within the second range. Examiner considers all elements in the multiple columns of the first matrix (output color matrix) to have been converted to color space with chromaticity coordinates (a*, b*)); and [determining a ratio of the average value of the first distances to the average value of the second distances and determining the saturation constraint regularization term based on a difference between the ratio and 1]. However, Wu does not explicitly disclose determining an average value of first distances between an origin [and chromaticity coordinates], determining an average value of second distances between the origin [and chromaticity coordinates], determining a ratio of the average value of the first distances to the average value of the second distances and determining the saturation constraint regularization term based on a difference between the ratio and 1. Chiba teaches determining an average value of first distances between an origin [and chromaticity coordinates] (See Chiba, ¶ [0037] the saturation increases as the radius from the origin increases. Examiner considers it to be obvious to one skilled in the art to measure all radii from all coordinates pairs to get the distance which gives saturation, as seen below in Fig. 2 for clarity), PNG media_image9.png 497 521 media_image9.png Greyscale determining an average value of second distances between the origin [and chromaticity coordinates] (See Chiba, ¶ [0037] the saturation increases as the radius from the origin increases. Examiner considers it to be obvious to one skilled in the art to measure all radii from all coordinates pairs to get the distance which gives saturation, as seen above in Fig. 2 for clarity), determining a ratio of the average value of the first distances to the average value of the second distances (See Chiba, ¶ [0037] the saturation increases as the radius from the origin increases. Examiner considers it to be obvious to one skilled in the art to measure all radii from all coordinates pairs to get the distance which gives saturation and then compare the two distances to form a ratio) and determining the saturation constraint regularization term based on a difference between the ratio and 1 (See Chiba, ¶ [0037] the saturation increases as the radius from the origin increases. Examiner considers it to be obvious to one skilled in the art to measure all radii from all coordinates pairs to get the distance which gives saturation and then compare the two distances to form a ratio. The value of 1 is considered to be the distance of the target color vector since the goal is to match the target color). Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Wu’s reference to determining an average value of first distances between an origin [and chromaticity coordinates], determining an average value of second distances between the origin [and chromaticity coordinates], determining a ratio of the average value of the first distances to the average value of the second distances and determining the saturation constraint regularization term based on a difference between the ratio and 1 based on the method of Chiba’s reference. The suggestion/motivation would have been since the Lab color space is a uniform color space that has good correlation with the human color perception with respect to distance of the coordinates as suggested by Chiba at ¶ [0047] and to match each of the hue-corrected colors C.sub.es', corresponding to the eighteen colors, to the corresponding goal colors as suggested by Chiba at ¶ [0043]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Chiba with Wu to obtain the invention as specified in claim 4. Regarding claim 12 (drawn to a device), claim 12 is rejected the same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to claim 12, and all the other limitations similar to claim 3 are not repeated herein, but incorporated by reference. Regarding claim 13 (drawn to a device), claim 13 is rejected the same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to claim 13, and all the other limitations similar to claim 4 are not repeated herein, but incorporated by reference. Regarding claim 18 (drawn to a non-transitory computer-readable storage medium), claim 18 is rejected the same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to claim 18, and all the other limitations similar to claim 3 are not repeated herein, but incorporated by reference. Regarding claim 19 (drawn to a non-transitory computer-readable storage medium), claim 19 is rejected the same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to claim 19, and all the other limitations similar to claim 4 are not repeated herein, but incorporated by reference. Claims 5-7, 14-16, 20, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Wu et al. (CN 112073703 A, hereinafter, Wu”, or "Wu Translation" corresponding to the translated document, or "Wu Original" corresponding to the original document ) in view of Cao (CN 111861922 A, hereinafter, “Cao”, or "Cao Translation" corresponding to the translated document, or "Cao Original" corresponding to the original document ). Regarding claim 5, in which claim 1 is incorporated, Wu discloses wherein before updating the color correction matrix based on the value of the loss function (See Wu Translation, ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix.; ¶ [0091] The original color correction matrix b is corrected by matrix a to obtain the target color correction matrix c. Examiner considers the selection of matrix a and correcting matrix b with matrix a as updating the color correction matrix), the method further comprises: [for the color correction matrix formed by a hue rotation matrix and a saturation scaling matrix,] [left-multiplying a mapping matrix from a luminance and chrominance (YUV) color space to a red, green, and blue (RGB) color space] [and right-multiplying a mapping matrix from the RGB color space to the YUV color space to obtain an initialized third-order color correction matrix; and] [representing one element in each row of elements in the initialized third-order color correction matrix by other two elements based on a white balance constraint to obtain the color correction matrix containing six variables;] and wherein updating the color correction matrix based on the value of the loss function (See Wu Translation, ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix.; ¶ [0091] The original color correction matrix b is corrected by matrix a to obtain the target color correction matrix c. Examiner considers the selection of matrix a and correcting matrix b with matrix a as updating the color correction matrix) comprises: [updating the six variables based on the value of the loss function to update the color correction matrix.] However, Wu does not explicitly disclose for the color correction matrix formed by a hue rotation matrix and a saturation scaling matrix, left-multiplying a mapping matrix from a luminance and chrominance (YUV) color space to a red, green, and blue (RGB) color space and right-multiplying a mapping matrix from the RGB color space to the YUV color space to obtain an initialized third-order color correction matrix; and representing one element in each row of elements in the initialized third-order color correction matrix by other two elements based on a white balance constraint to obtain the color correction matrix containing six variables; updating the six variables based on the value of the loss function to update the color correction matrix. Cao teaches for the color correction matrix formed by a hue rotation matrix (See Cao Translation, ¶ [0057] the process of performing coordinate transformation on the transformation matrix for image chromaticity rotation in the YUV color space, may include: left-multiplying the transformation matrix T_O based on the YUV color space by the rotation transformation matrix R; See Cao Original, ¶ [0053], PNG media_image10.png 266 596 media_image10.png Greyscale . Examiner considers matrix R to be a hue rotation matrix) and a saturation scaling matrix (See Cao Translation, ¶ [0056] the process of performing coordinate transformation on the transformation matrix in the YUV color space for adjusting image saturation, may include: left-multiplying the transformation matrix T_O based on the YUV color space by the scaling transformation matrix S; See Cao Original, ¶ [0053], PNG media_image11.png 322 457 media_image11.png Greyscale . Examiner considers the S matrix to be a saturation scaling matrix), left-multiplying a mapping matrix from a luminance and chrominance (YUV) color space to a red, green, and blue (RGB) color space (See Cao Translation. ¶ [0060] Step S2081: Multiply the transformation matrix T based on the YUV color space after coordinate transformation by the second mapping matrix on the left and by the first mapping matrix on the right to obtain the final color correction matrix … The first mapping matrix is the RGB to YUV conversion matrix rgb2yuv, the second mapping matrix is the YUV to RGB conversion matrix yuv2rgb) and right-multiplying a mapping matrix from the RGB color space to the YUV color space (See Cao Translation, ¶ [0060] Step S2081: Multiply the transformation matrix T based on the YUV color space after coordinate transformation by the second mapping matrix on the left and by the first mapping matrix on the right to obtain the final color correction matrix … The first mapping matrix is the RGB to YUV conversion matrix rgb2yuv, the second mapping matrix is the YUV to RGB conversion matrix yuv2rgb) to obtain an initialized third-order color correction matrix (See Cao Translation, ¶ [0126] Specifically, the CCM is left-multiplied by the rgb2yuv matrix subsequently used by the isp, and then right-multiplied by its yuv2rgb matrix, which is the rgb2yuv inverse matrix. The obtained YUV transformation matrix; See Cao Original, ¶ [0122] PNG media_image12.png 331 574 media_image12.png Greyscale . Examiner considers matrix T to be an initialized third order color correction matrix); and representing one element in each row of elements in the initialized third-order color correction matrix by other two elements based on a white balance constraint (See Cao Translation, ¶ [0113] manual white balance correction) to obtain the color correction matrix containing six variables (See Cao Translation, ¶ [0126] Specifically, the CCM is left-multiplied by the rgb2yuv matrix subsequently used by the isp, and then right-multiplied by its yuv2rgb matrix, which is the rgb2yuv inverse matrix. The obtained YUV transformation matrix. Examiner considers it to be obvious to one skilled in the art to rewrite elements in relation to other elements in the same row as long as each row adds to the white balance constraint); updating the six variables based on the value of the loss function to update the color correction matrix (See Cao Translation, ¶ [0126] Specifically, the CCM is left-multiplied by the rgb2yuv matrix subsequently used by the isp, and then right-multiplied by its yuv2rgb matrix, which is the rgb2yuv inverse matrix. The obtained YUV transformation matrix. Examiner considers it to be obvious to one skilled in the art to rewrite elements in relation to other elements in the same row as long as each row adds to the white balance constraint and then update the matrix accordingly). Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Wu’s reference for the color correction matrix formed by a hue rotation matrix and a saturation scaling matrix, left-multiplying a mapping matrix from a luminance and chrominance (YUV) color space to a red, green, and blue (RGB) color space and right-multiplying a mapping matrix from the RGB color space to the YUV color space to obtain an initialized third-order color correction matrix; and representing one element in each row of elements in the initialized third-order color correction matrix by other two elements based on a white balance constraint to obtain the color correction matrix containing six variables; updating the six variables based on the value of the loss function to update the color correction matrix based on the method of Cao’s reference. The suggestion/motivation would have been for adjusting image saturation and for rotating image chroma for coordinate transformation as suggested by Cao at ¶ [0016] and to maintain consistency with the ISP process and obtain the original image as suggested by Cao at ¶ [0113], a process which takes place before updating the correction matrix. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Cao with Wu to obtain the invention as specified in claim 5. Regarding claim 6, in which claim 1 is incorporated, Wu discloses wherein an initialization process of the color correction matrix (See Wu Translation, ¶ [0051] You can directly capture the uncorrected image to obtain the color chart image, and then use the steps in S102-S104 to obtain the correction matrix) comprises one of the following: [determining a hue rotation factor and a saturation scaling factor based on a value range of the hue rotation factor in the hue rotation matrix and a value range of the saturation scaling factor in the saturation scaling matrix and determining at least two color correction matrixes based on the hue rotation factor and the saturation scaling factor;] [or randomly generating at least two sets of hue rotation factors and saturation scaling factors based on a probability distribution model of the hue rotation factors and the saturation scaling factors and determining at least two color correction matrixes based on the at least two sets of hue rotation factors and saturation scaling factors.] However, Wu does not explicitly disclose determining a hue rotation factor and a saturation scaling factor based on a value range of the hue rotation factor in the hue rotation matrix and a value range of the saturation scaling factor in the saturation scaling matrix and determining at least two color correction matrixes based on the hue rotation factor and the saturation scaling factor; or randomly generating at least two sets of hue rotation factors and saturation scaling factors based on a probability distribution model of the hue rotation factors and the saturation scaling factors and determining at least two color correction matrixes based on the at least two sets of hue rotation factors and saturation scaling factors. Cao teaches determining a hue rotation factor and a saturation scaling factor based on a value range of the hue rotation factor in the hue rotation matrix and a value range of the saturation scaling factor in the saturation scaling matrix and determining at least two color correction matrixes based on the hue rotation factor and the saturation scaling factor; or randomly generating at least two sets of hue rotation factors and saturation scaling factors based on a probability distribution model of the hue rotation factors and the saturation scaling factors and determining at least two color correction matrixes based on the at least two sets of hue rotation factors and saturation scaling factors (See Cao Translation, ¶ [0056] scaling transformation matrix S; ¶ [0057] rotation transformation matrix R; ¶ [0060] Lab is a device-independent color model and also a color model based on physiological Characteristics… The L, a, and b values can be used to quantify the colors in an image; See Cao Original, ¶ [0053], PNG media_image13.png 312 443 media_image13.png Greyscale , PNG media_image14.png 255 572 media_image14.png Greyscale . Examiner considers one to be able to randomly select two sets from each matrix, (s1 and s2) and (sin and -sin). Further the Examiner considers the lab color model as a distribution model or a visual model of different possible colors. The claim states, “one of the following” and the Examiner has cited to address “randomly generating”). Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Wu’s reference to randomly generating at least two sets of hue rotation factors and saturation scaling factors based on a probability distribution model of the hue rotation factors and the saturation scaling factors and determining at least two color correction matrixes based on the at least two sets of hue rotation factors and saturation scaling factors based on the method of Cao’s reference. The suggestion/motivation would have been for adjusting image saturation and for rotating image chroma for coordinate transformation as suggested by Cao at ¶ [0016] and since lab color space is a uniform color space that has good correlation with the human color perception as suggested by Cao at ¶ [0037]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Cao with Wu to obtain the invention as specified in claim 6. Regarding claim 7, in which claim 6 is incorporated, Wu discloses wherein performing correction processing on a color source matrix of an acquired color chart image (See Wu Translation, ¶ [0051] You can directly capture the uncorrected image to obtain the color chart image, and then use the steps in S102-S104 to obtain the correction matrix. Examiner considers the uncorrected image (considered to be the color chart matrix) to be used for a correction process (considered to be steps S102-S104) to get a correction matrix (considered to be a target or original correction matrix that needs optimizing)) based on a color correction matrix (See Wu Translation, ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix. Examiner considers the matrix ‘a’ to be the color correction matrix) to obtain an output color matrix (See Wu Translation, ¶ [0072] Specifically, the RGB values of each deviation color block in the RGB format color chart image can be obtained, and then the first matrix can be built based on the RGB values). Examiner considers the first matrix as the output color matrix) comprises: performing correction processing on a color source matrix of an acquired color chart image (See Wu Translation, ¶ [0051] You can directly capture the uncorrected image to obtain the color chart image, and then use the steps in S102-S104 to obtain the correction matrix. Examiner considers the uncorrected image (considered to be the color chart matrix) to be used for a correction process (considered to be steps S102-S104) to get a correction matrix (considered to be a target or original correction matrix that needs optimizing)) [based on the at least two color correction matrixes to obtain at least two output color matrixes; and] wherein updating the color correction matrix based on the value of the loss function until the value of the loss function converges to obtain the optimal color correction matrix (See Wu Translation, ¶ [0085] However, the above formula can yield multiple matrices 'a', which need to be filtered; ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix; ¶ [0091] The original color correction matrix b is corrected by matrix a to obtain the target color correction matrix c. Examiner considers the selection of matrix a and correcting matrix b with matrix a as updating the color correction matrix. Multiple matrices are generated and thus it is a repetitive process until the matrix a that minimizes the loss value is selected) comprises: [optimizing the at least two color correction matrixes] based on the value of the loss function until the value of the loss function converges to a minimum value to obtain at least two minimum values (See Wu Translation, ¶ [0085] yield multiple matrices 'a'; ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix. Examiner considers there to be multiple matrices produced with each having their own values. Among the multiple matrices, there must be at least 2 with the lowest value); and determining a smallest value of the at least two minimum values and using the updated color correction matrix corresponding to the smallest value as the optimal color correction matrix (See Wu Translation, ¶ [0085] yield multiple matrices 'a'; ¶ [0088] the matrix 'a' that minimizes the loss value can be selected as the correction matrix. Examiner considers there to be multiple matrices produced with each having their own values. Among the multiple matrices, there must be at least 2 with the lowest value. The matrix with the lowest, minimal, value is chosen as the correction matrix, or as the optimal correction matrix). However, Wu does not explicitly disclose [performing correction processing on a color source matrix of an acquired color chart image] based on the at least two color correction matrixes to obtain at least two output color matrixes; and optimizing the at least two color correction matrixes [based on the value of the loss function until the value of the loss function converges to a minimum value to obtain at least two minimum values]. Cao teaches [performing correction processing on a color source matrix of an acquired color chart image] based on the at least two color correction matrixes to obtain at least two output color matrixes (See Cao Translation, ¶ [0056] scaling transformation matrix S; ¶ [0057] rotation transformation matrix R. Examiner considers one to be able to randomly select two sets from each matrix ,(s1 and s2) and (sin and -sin). The factors can be formed into a matrix to then get two color correction matrices); and optimizing the at least two color correction matrixes (See Cao Translation, ¶ [0056] scaling transformation matrix S; ¶ [0057] rotation transformation matrix R. Examiner considers one to be able to randomly select two sets from each matrix ,(s1 and s2) and (sin and -sin). The factors can be formed into a matrix to then get two color correction matrices which are then used to get an optimal correction matrix; thus, the matrices themselves are also optimized) [based on the value of the loss function until the value of the loss function converges to a minimum value to obtain at least two minimum values]. Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Wu’s reference to performing correction processing on a color source matrix of an acquired color chart image] based on the at least two color correction matrixes to obtain at least two output color matrixes; and optimizing the at least two color correction matrixes [based on the value of the loss function until the value of the loss function converges to a minimum value to obtain at least two minimum values] based on the method of Cao’s reference. The suggestion/motivation would have been for adjusting image saturation and for rotating image chroma to adjust the color correction matrix as suggested by Cao at ¶ [0125]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine Cao with Wu to obtain the invention as specified in claim 7. Regarding claim 14 (drawn to a device), claim 14 is rejected the same as claim 5 and the arguments similar to that presented above for claim 5 are equally applicable to claim 14, and all the other limitations similar to claim 5 are not repeated herein, but incorporated by reference. Regarding claim 15 (drawn to a device), claim 15 is rejected the same as claim 6 and the arguments similar to that presented above for claim 6 are equally applicable to claim 15, and all the other limitations similar to claim 6 are not repeated herein, but incorporated by reference. Regarding claim 16 (drawn to a device), claim 16 is rejected the same as claim 7 and the arguments similar to that presented above for claim 7 are equally applicable to claim 16, and all the other limitations similar to claim 7 are not repeated herein, but incorporated by reference. Regarding claim 20 (drawn to a non-transitory computer-readable storage medium), claim 20 is rejected the same as claim 5 and the arguments similar to that presented above for claim 5 are equally applicable to claim 20, and all the other limitations similar to claim 5 are not repeated herein, but incorporated by reference. Regarding claim 21 (drawn to a non-transitory computer-readable storage medium), claim 21 is rejected the same as claim 6 and the arguments similar to that presented above for claim 6 are equally applicable to claim 21, and all the other limitations similar to claim 6 are not repeated herein, but incorporated by reference. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Wu et al. (US 20240282007 A1) discloses a method for generating a color correction model. Color coordinates are converted into a RBG color space and an XYZ color space. An initial color correction model trained according to sample output data and reference output data. The trained color correction model is then used to perform a correction process on a target pixel based on XYZ coordinates which is beneficial to improving the accuracy of color correction. Messer et al. (US 20210407365 A1) discloses a method to improve color uniformity of a display. At the pixel level, it is often difficult to capture the intensity of an additive color. Multiple images are taken and then normalized using a global white balance function. The images are then transformed into multiple weighted matrices. Through this technique, correction of high levels of color non-uniformity can be achieved. Yang (CN 113947533 A) discloses a method for image color correction. An image that needs correction is processed to obtain a color element value. A standard image is used as reference for the true restoration of image colors. Color elements are converted into the LAB color space and used to measure the difference between the image and the standard image. An initial color correction matrix is established but is converged with the directional constraint of the image color element value and the standard color element value. Convergence with a set direction improves the accuracy of the color correction process. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jasmin Marcelino Hernandez whose telephone number is (571)270-0211. The examiner can normally be reached 7am-3pm EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Henok Shiferaw can be reached at (571) 272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JASMIN MARCELINO HERNAND/Examiner, Art Unit 2676 /Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676