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 .
Priority
Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Election/Restrictions
Claims 3-5, 7-13, and 16-18 are withdrawn at this time from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected species, there being no allowable generic or linking claim. The Office acknowledges applicant’s timely election with traversed the restriction requirement in the reply filed on 07/15/2025.
Claims 1-2, 6, 14-15, and 19-20 are being examined, since elected by the applicant as the claims with the elected species.
The applicant argues on page 10, “The four types of adjustment strategies do not have mutually independent or unrelated improvement objectives, can be used individually or in combination based on the characteristics of the original image characteristic and types of color blindness, and there are no mutually exclusive technical features. Pursuant to MPEP § 806.04, a plurality of embodiments under the same general concept should not be directly deemed to constitute technical solutions with patentable distinction. Furthermore, examining claims 1, 2, 3, 4, 5, 6, 14, 15, 16, 17, 18, 19 and 20 would not result in the significant search burden alleged in the office action.”
In response, the Office does not find this argument to be persuasive. There is a search and/or examination burden for the patentably distinct species/sub-species as set forth above because at least the following reason(s) apply: Each species and subspecies require different search terms to be formulated along with the interpretation of the claims. The species and sub-species require a different field of search (e.g., searching different classes/subclasses or electronic resources, or employing different search strategies or search queries). Serious burden may be established based on different search strategies if it is necessary to search for one of the species/sub-species that would not likely result in finding art relevant to the other species/sub-species. Different terminology would be required to be employed to search for the elected species and the non-elected species, resulting in a serious search burden on the Office.
The Office would like to thank the applicant for electing Sub-species A2, which includes claims 1-2, 6, 14-15, and 19-20 as originally filed, as it enhances efficiency in the examination process and allows for prosecution to be conducted in a timely manner and move closer towards potential protection/allowance.
Specification Objections
The specification is objected to because of the following informalities:
On Page 1, line 27, “to allow colors in the original image can be distinguished by a color-blind user” should read “to allow colors in the original image to be distinguished by a color-blind user” in order to avoid a typographical and grammatical error.
On Page 7, line 23, “the method includes at least steps S1 to S3.” should read “the method includes at least steps S1 to S4.” in order to avoid a typographical and grammatical error.
On Page 19, line 31, “to allow color-blind users can distinguish among colors” should read “to allow color-blind users to distinguish among colors” in order to avoid a typographical and grammatical error.
On Page 22, line 5, “to allow colors in the original image can be distinguished by a color-blind user.” should read “to all colors in the original image to be distinguished by a color-blind user.” in order to avoid a typographical and grammatical error.
On Page 23, line 19, “to all colors in the original image can be distinguished by a color-blind user.” should read “to all colors in the original image to be distinguished by a color-blind user.” in order to avoid a typographical and grammatical error.
Appropriate correction is required.
Claim Objections
Claim 14 is objected to because of the following informalities:
In claim 14, line 3, the term “connection with at least one processor” should be changed to “connection with the at least one processor” in order to avoid an insufficient antecedent issue and prevent a rejection under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph issues.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 20 along with its dependent claims are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 20 is drawn to a computer readable storage medium having a computer program stored thereon, wherein the computer program when executed, implements the image correction method as defined in the specification in paragraph [00107]- “As to the specification, “the computer readable medium” may be any device adaptive for including, storing, communicating, propagating or transferring programs to be used by or in combination with the instruction execution system, device or equipment. More specific examples of the computer readable medium include but are not limited to: an electronic connection (an electronic device) with one or more wires, a portable computer enclosure (a magnetic device), a random access memory (RAM), a read only memory (ROM), an erasable programmable read-only memory (EPROM or a flash memory), an optical fiber device and a portable compact disk read-only memory (CDROM). In addition, the computer readable medium may even be a paper or other appropriate medium capable of printing programs thereon, this is because, for example, the paper or other appropriate medium may be optically scanned and then edited, decrypted or processed with other appropriate methods when necessary to obtain the programs in an electric manner, and then the programs may be stored in the computer memories.” Thus, explicitly defined to encompass both transitory and non-transitory, can be a signal or carrier wave etc; therefore, fail(s) to fall within at least one of the four categories of patent eligible subject matter. It has been understood by the office that the computer readable storage medium is the same as "computer readable medium". Therefore claim 20 does not fit within the recognized categories of statutory subject matter. See MPEP 2106.
The office respectfully recommends the applicant to amend claim 20 limitation “A non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor, implements the image correction method according to claim 1.”
Claim Rejections - 35 USC § 103
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 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.
Claims 1, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over OLSEN et al. (US 20230016631 A1), hereinafter referenced as OLSEN, in view of ZHOU et al. (US 20230410380 A1), hereinafter referenced as ZHOU.
Regarding claim 1, OLSEN explicitly teaches an image correction method (Fig. 1A-1B. Paragraph [0039]-OLSEN discloses the method modifies the color of received images based upon user color blindness information received from a user and based on the color gamut of the display.), comprising:
obtaining an original image (Fig. 1A-1B. Paragraph [0039]-OLSEN discloses the method modifies the color of received images based upon user color blindness information received from a user and based on the color gamut of the display (wherein receiving images is obtaining images).) and a preset color adjustment strategy (Fig. 1A-1B. Paragraph [0045]-OLSEN discloses the method identifies pixels including 1931 CIE xy color coordinates within a pre-established filter area (104) corresponding to a region of the CIE color space where a color blind viewer will experience reduced color perception, and flags the identified pixels. The method adjusts flagged pixel color information by translating (106) flagged pixel color coordinates (e.g., (x.sub.1, y.sub.1)) within the CIE color space to a second color coordinate (e.g., (x.sub.2, y.sub.2)) away from a confusion line (wherein flagging and translating is a preset color adjustment strategy).);
obtaining pixel statistical information of the original image (Fig. 1A-1B. Paragraph [0045]-OLSEN discloses the method adjusts flagged pixel color information by translating (106) flagged pixel color coordinates (e.g., (x.sub.1, y.sub.1)) within the CIE color space to a second color coordinate (e.g., (x.sub.2, y.sub.2)) away from a confusion line (wherein pixel information is pixel statistical information).);
OLSEN fails to explicitly teach determining a target color adjustment strategy based on the pixel statistical information and the preset color adjustment strategy; and adjusting the original image based on the target color adjustment strategy to obtain a target image with colors distinguishable by a user.
However, ZHOU explicitly teaches determining a target color adjustment strategy (Fig. 2. Paragraph [0042]-ZHOU discloses Step 203, generating, in response to determining that the simulated color information of the target element satisfies a preset condition, target color information of the target element, using a second color transformation strategy, based on the initial color information of the target element, the present condition representing a degree of friendliness of the simulated color to the characteristic population (wherein the target color adjustment strategy is the second color transformation strategy, wherein color information is the pixel statistical information, and wherein the preset color adjustment strategy is the first color transformation strategy which determined the simulated color information).) based on the pixel statistical information (Fig. 2. Paragraph [0035]-ZHOU discloses the initial color information of the target element includes an initial color of the text and an initial color of the block where the text is located (i.e., a background color of the text). For example, color may be represented in the form of R (red), G (green), B (blue) components. The size information of the target element includes size information of the text and size information of the block where the text is located. For example, a length and width of the text and the block may be represented in a form of pixel number.) and the preset color adjustment strategy (Fig. 2. Paragraph [0040]-ZHOU discloses the first color transformation strategy is used to represent a corresponding relationship between the initial color and the simulated color, for example, it may be a color blindness simulation matrix.); and
adjusting the original image based on the target color adjustment strategy to obtain a target image (Fig. 2. Paragraph [0049]-ZHOU discloses redrawing the target element based on the target color information and the size information to obtain a target page (wherein the target element is the original image and the target page is the target image).) with colors distinguishable by a user (Fig. 2. Paragraph [0043]-ZHOU discloses the second color transformation strategy is used to represent a corresponding relationship between the initial color and the target color, and the target color represents a color that is easily recognized to the characteristic population.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of OLSEN of an image correction method, comprising: obtaining an original image and a preset color adjustment strategy; obtaining pixel statistical information of the original image with the teachings of ZHOU of determining a target color adjustment strategy based on the pixel statistical information and the preset color adjustment strategy; and adjusting the original image based on the target color adjustment strategy to obtain a target image with colors distinguishable by a user.
Wherein having OLSEN’s method for image color correction for the remediation of color blindness having determining a target color adjustment strategy based on the pixel statistical information and the preset color adjustment strategy; and adjusting the original image based on the target color adjustment strategy to obtain a target image with colors distinguishable by a user.
The motivation behind the modification would have been to obtain a method for image color correction for the remediation of color blindness that reduces color confusion of a user and enhances the efficiency of the method. Since both OLSEN and ZHOU relate to remediating color blindness through color correction via a computer, wherein OLSEN for modifying the color of individual pixels in a displayed image to reduce color confusion for users experiencing color blindness, while ZHOU may simplify the process of color optimization and improve an efficiency of color optimization. Please see OLSEN et al. (US 20230016631 A1), Paragraph [0007], and ZHOU et al. (US 20230410380 A1), Paragraph [0061].
Regarding claim 14, OLSEN in view of ZHOU explicitly teach the image correction method according to claim 1.
OLSEN further explicitly teaches an electronic device (Fig. 9. Paragraph [0106]-OLSEN discloses FIG. 9 shows an example of a computing device 900 and a mobile computing device 950 that can be used as data processing apparatuses to implement the techniques described. The computing device 900 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers.), comprising:
at least one processor (Fig. 9, #902 called processor. Paragraph [0107]-OLSEN discloses the computing device 900 includes a processor 902.); and
a memory (Fig. 9, #904 called memory. Paragraph [0108]-OLSEN discloses the memory 904 stores information within the computing device 900.) in communication connection with at least one processor (Fig. 9. Paragraph [0107]-OLSEN discloses the processor 902 can process instructions for execution within the computing device 900, including instructions stored in the memory 904 or on the storage device 906 to display graphical information for a GUI on an external input/output device, such as a display 916 coupled to the high-speed interface 908.),
wherein the memory stores a computer program executable by the at least one processor (Fig. 9. Paragraph [0107]-OLSEN discloses the processor 902 can process instructions for execution within the computing device 900, including instructions stored in the memory 904 or on the storage device 906 to display graphical information for a GUI on an external input/output device, such as a display 916 coupled to the high-speed interface 908.), and the at least one processor is configured to perform the computer program to implement (Fig. 9. Paragraph [0107]-OLSEN discloses the processor 902 can process instructions for execution within the computing device 900, including instructions stored in the memory 904 or on the storage device 906 to display graphical information for a GUI on an external input/output device, such as a display 916 coupled to the high-speed interface 908.)
Regarding claim 20, OLSEN in view of ZHOU explicitly teach the image correction method according to claim 1.
OLSEN further explicitly teaches a computer readable storage medium having a computer program stored thereon, wherein the computer program when executed (Fig. 9, #904 called memory. Paragraph [0107]-OLSEN discloses the processor 902 can process instructions for execution within the computing device 900, including instructions stored in the memory 904 or on the storage device 906 to display graphical information for a GUI on an external input/output device, such as a display 916 coupled to the high-speed interface 908.),
Claims 2 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over OLSEN et al. (US 20230016631 A1), hereinafter referenced as OLSEN, in view of ZHOU et al. (US 20230410380 A1), hereinafter referenced as ZHOU, and further in view of, LIU et al. (US 20210183029 A1), hereinafter referenced as LIU.
Regarding claim 2, OLSEN in view of ZHOU explicitly teach the image correction method according to claim 1,
OLSEN further explicitly teaches wherein the preset color adjustment strategy comprises a first color adjustment strategy (Fig. 1A-1B. Paragraph [0045]-OLSEN discloses the method identifies pixels including 1931 CIE xy color coordinates within a pre-established filter area (104) corresponding to a region of the CIE color space where a color blind viewer will experience reduced color perception, and flags the identified pixels. The method adjusts flagged pixel color information by translating (106) flagged pixel color coordinates (e.g., (x.sub.1, y.sub.1)) within the CIE color space to a second color coordinate (e.g., (x.sub.2, y.sub.2)) away from a confusion line (wherein flagging and translating is a first color adjustment strategy).),
OLSEN fails to explicitly teach the first color adjustment strategy is obtained by: obtaining coordinate information of a white point in u'v' space, coordinate information of a pixel to be adjusted in the original image, and a first rotation angle value of the pixel to be adjusted; obtaining, based on the coordinate information of the white point and the coordinate information of the pixel to be adjusted, a first angle value between the pixel to be adjusted and the white point, as well as a first distance value between the pixel to be adjusted and the white point; and obtaining adjusted coordinate information corresponding to the pixel to be adjusted in the original image based on the coordinate information of the white point, the first rotation angle value, the first angle value and the first distance value.
However, LIU explicitly teaches the first color adjustment strategy is obtained by (Fig. 3. Paragraph [0039]-LIU discloses a corrected color coordinate of the pixel based on a set of offsets of an original color coordinate of the pixel in the original color gamut relative to the set of original primary color directions and the set of primary color direction deviations is determined.):
obtaining coordinate information of a white point in u'v' space (Fig. 1 and 4, illustrate a white point W in u’v’ color space. Paragraph [0045]-LIU discloses an intersection point of the straight line WP.sub.0 connecting the white point W and the original color coordinate P.sub.0 and the boundary of the color gamut BT.2020 is denoted as point a, and another intersection point of the straight line WP.sub.0 and the boundary of the color gamut BT.709 is denoted as point b. Further in paragraph [0047]-LIU discloses the white point W has a coordinate (u.sub.w, v.sub.w).), coordinate information of a pixel to be adjusted (Fig. 4. Paragraph [0044]-LIU discloses assuming that a pixel has an original color coordinate P.sub.0 which is between the green direction WGh and the blue direction WBh.) in the original image (Fig. 1. Paragraph [0018]-LIU discloses the original image represented in the BT.2020 format needs to be processed to be converted to a target image represented in the BT.709 format.), and a first rotation angle value of the pixel to be adjusted (Fig. 5, illustrates a rotation angle value of the pixel to be adjusted denoted by angle Dg. Paragraph [0042]-LIU discloses the green direction deviation Dg in substance corresponds to a maximum rotational angle between two vertexes Gh and Gh′. Paragraph [0025]-LIU discloses each pixel in the original image has a color represented by an original color coordinate in the original color gamut, such as a coordinate of the green vertex Gh or another color coordinate P.sub.0.);
obtaining, based on the coordinate information of the white point (Fig. 1 and 4, illustrate a white point W in u’v’ color space. Paragraph [0045]-LIU discloses an intersection point of the straight line WP.sub.0 connecting the white point W and the original color coordinate P.sub.0 and the boundary of the color gamut BT.2020 is denoted as point a, and another intersection point of the straight line WP.sub.0 and the boundary of the color gamut BT.709 is denoted as point b. Further in paragraph [0047]-LIU discloses the white point W has a coordinate (u.sub.w, v.sub.w).) and the coordinate information of the pixel to be adjusted (Fig. 4. Paragraph [0044]-LIU discloses assuming that a pixel has an original color coordinate P.sub.0 which is between the green direction WGh and the blue direction WBh.), a first angle value between the pixel to be adjusted and the white point (Fig. 5, illustrates a first angle value between the pixel to be adjusted and the white point denoted by angle D. Paragraph [0045]-LIU discloses the mapping Equation (3) below can be used for calculating the offset, which, however, can be appreciated as an exemplary equation for the calculation. tan_d=(tan_green*dist_Bh_a+tan_blue*dist_Gh_a)/(dist_Bh_a+dist_Gh_a) (3) wherein tan_d denotes the tangent value of a correction angle D (an angular difference between the correction direction WP.sub.1 and the original direction WP.sub.0), dist_Bh_a denotes a length of the segment Bha and dist_Gh_a denotes a length of the segment Gha.), as well as a first distance value between the pixel to be adjusted and the white point (Fig. 5. Paragraph [0060]-LIU discloses a distance from the corrected color coordinate P.sub.1 to the white point W is WP.sub.1.); and
obtaining adjusted coordinate information (Fig. 4-5. Paragraph [0029]-LIU discloses the corrected color direction and the corrected color coordinate P.sub.1for P.sub.0 can be calculated based on the two primary color direction deviations and the original color coordinate P.sub.0.) corresponding to the pixel to be adjusted in the original image (Fig. 4. Paragraph [0044]-LIU discloses assuming that a pixel has an original color coordinate P.sub.0 which is between the green direction WGh and the blue direction WBh.) based on the coordinate information of the white point (Fig. 4. Paragraph [0047]-LIU discloses the corrected color coordinate P1 can be further calculated using Equation (4) below with the correction angle D taken into account, i.e. the original color coordinate P.sub.0(u.sub.p0, v.sub.p0) is corrected to the coordinate P.sub.1(u.sub.p1, v.sub.p1) shown in FIG. 4. u.sub.p1=(u.sub.p0−u.sub.w)*cosD−(v.sub.p0−v.sub.w)*sinD+u.sub.w v.sub.p1=(v.sub.p0−v.sub.w)*cosD+(u.sub.p0−u.sub.w)*sinD+v.sub.w (4) wherein the white point W has a coordinate (u.sub.w, v.sub.w), D denotes the correction angle.), the first rotation angle value (Fig. 4. Paragraph [0051]-LIU discloses the correction angle D can be calculated based on the green direction deviation Dg.), the first angle value (Fig. 5, illustrates a first angle value between the pixel to be adjusted and the white point denoted by angle D. Paragraph [0045]-LIU discloses the mapping Equation (3) below can be used for calculating the offset, which, however, can be appreciated as an exemplary equation for the calculation. tan_d=(tan_green*dist_Bh_a+tan_blue*dist_Gh_a)/(dist_Bh_a+dist_Gh_a) (3) wherein tan_d denotes the tangent value of a correction angle D (an angular difference between the correction direction WP.sub.1 and the original direction WP.sub.0), dist_Bh_a denotes a length of the segment Bha and dist_Gh_a denotes a length of the segment Gha.) and the first distance value (Fig. 5. Paragraph [0059-0060]-LIU discloses the coordinate P.sub.1 can be mapped to the coordinate P.sub.2 in the color gamut BT.709 using a non-linear mapping algorithm. The mapping ratio can be calculated using the following method. First, a first compression parameterC.sub.1 is calculated. It is assumed that a distance from the white point W to a point a′ (u.sub.a′,v.sub.a′) on the boundary of the color gamut BT.2020 is Wa′, and a distance from the white point W to a point b′ (u.sub.b′,v.sub.b′) on the boundary of the color gamut BT.709 is Wb′, and a distance from the corrected color coordinate P.sub.1 to the white point W is WP.sub.1.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of OLSEN in view of ZHOU of an image correction method, comprising: obtaining an original image and a preset color adjustment strategy; obtaining pixel statistical information of the original image with the teachings of LIU of the first color adjustment strategy is obtained by: obtaining coordinate information of a white point in u'v' space, coordinate information of a pixel to be adjusted in the original image, and a first rotation angle value of the pixel to be adjusted; obtaining, based on the coordinate information of the white point and the coordinate information of the pixel to be adjusted, a first angle value between the pixel to be adjusted and the white point, as well as a first distance value between the pixel to be adjusted and the white point; and obtaining adjusted coordinate information corresponding to the pixel to be adjusted in the original image based on the coordinate information of the white point, the first rotation angle value, the first angle value and the first distance value.
Wherein having OLSEN’s method for image color correction for the remediation of color blindness having the first color adjustment strategy is obtained by: obtaining coordinate information of a white point in u'v' space, coordinate information of a pixel to be adjusted in the original image, and a first rotation angle value of the pixel to be adjusted; obtaining, based on the coordinate information of the white point and the coordinate information of the pixel to be adjusted, a first angle value between the pixel to be adjusted and the white point, as well as a first distance value between the pixel to be adjusted and the white point; and obtaining adjusted coordinate information corresponding to the pixel to be adjusted in the original image based on the coordinate information of the white point, the first rotation angle value, the first angle value and the first distance value.
The motivation behind the modification would have been to obtain a method for image color correction for the remediation of color blindness that reduces color confusion of a user and enhances the efficiency of the method. Since both OLSEN and LIU relate to image color correction in CIE color space, wherein OLSEN for modifying the color of individual pixels in a displayed image to reduce color confusion for users experiencing color blindness, while LIU to improve the conventional HDR to SDR conversion. Please see OLSEN et al. (US 20230016631 A1), Paragraph [0007], and LIU et al. (US 20210183029 A1), Paragraph [0004].
Regarding claim 15, OLSEN in view of ZHOU explicitly teach the electronic device according to claim 14,
OLSEN further explicitly teaches wherein the preset color adjustment strategy comprises a first color adjustment strategy (Fig. 1A-1B. Paragraph [0045]-OLSEN discloses the method identifies pixels including 1931 CIE xy color coordinates within a pre-established filter area (104) corresponding to a region of the CIE color space where a color blind viewer will experience reduced color perception, and flags the identified pixels. The method adjusts flagged pixel color information by translating (106) flagged pixel color coordinates (e.g., (x.sub.1, y.sub.1)) within the CIE color space to a second color coordinate (e.g., (x.sub.2, y.sub.2)) away from a confusion line (wherein flagging and translating is a first color adjustment strategy).),
the at least one processor is further configured to perform the computer program to (Fig. 9. Paragraph [0107]-OLSEN discloses the processor 902 can process instructions for execution within the computing device 900, including instructions stored in the memory 904 or on the storage device 906 to display graphical information for a GUI on an external input/output device, such as a display 916 coupled to the high-speed interface 908.):
OLSEN fails to explicitly teach obtain coordinate information of a white point in u'v' space, coordinate information of a pixel to be adjusted in the original image, and a first rotation angle value of the pixel to be adjusted; obtain, based on the coordinate information of the white point and the coordinate information of the pixel to be adjusted, a first angle value between the pixel to be adjusted and the white point, as well as a first distance value between the pixel to be adjusted and the white point; and obtain adjusted coordinate information corresponding to the pixel to be adjusted in the original image based on the coordinate information of the white point, the first rotation angle value, the first angle value and the first distance value.
However, LIU explicitly teaches obtain coordinate information of a white point in u'v' space (Fig. 1 and 4, illustrate a white point W in u’v’ color space. Paragraph [0045]-LIU discloses an intersection point of the straight line WP.sub.0 connecting the white point W and the original color coordinate P.sub.0 and the boundary of the color gamut BT.2020 is denoted as point a, and another intersection point of the straight line WP.sub.0 and the boundary of the color gamut BT.709 is denoted as point b. Further in paragraph [0047]-LIU discloses the white point W has a coordinate (u.sub.w, v.sub.w).), coordinate information of a pixel to be adjusted (Fig. 4. Paragraph [0044]-LIU discloses assuming that a pixel has an original color coordinate P.sub.0 which is between the green direction WGh and the blue direction WBh.) in the original image (Fig. 1. Paragraph [0018]-LIU discloses the original image represented in the BT.2020 format needs to be processed to be converted to a target image represented in the BT.709 format.), and a first rotation angle value of the pixel to be adjusted (Fig. 5, illustrates a rotation angle value of the pixel to be adjusted denoted by angle Dg. Paragraph [0042]-LIU discloses the green direction deviation Dg in substance corresponds to a maximum rotational angle between two vertexes Gh and Gh′. Paragraph [0025]-LIU discloses each pixel in the original image has a color represented by an original color coordinate in the original color gamut, such as a coordinate of the green vertex Gh or another color coordinate P.sub.0.);
obtain, based on the coordinate information of the white point (Fig. 1 and 4, illustrate a white point W in u’v’ color space. Paragraph [0045]-LIU discloses an intersection point of the straight line WP.sub.0 connecting the white point W and the original color coordinate P.sub.0 and the boundary of the color gamut BT.2020 is denoted as point a, and another intersection point of the straight line WP.sub.0 and the boundary of the color gamut BT.709 is denoted as point b. Further in paragraph [0047]-LIU discloses the white point W has a coordinate (u.sub.w, v.sub.w).) and the coordinate information of the pixel to be adjusted (Fig. 4. Paragraph [0044]-LIU discloses assuming that a pixel has an original color coordinate P.sub.0 which is between the green direction WGh and the blue direction WBh.), a first angle value between the pixel to be adjusted and the white point (Fig. 5, illustrates a first angle value between the pixel to be adjusted and the white point denoted by angle D. Paragraph [0045]-LIU discloses the mapping Equation (3) below can be used for calculating the offset, which, however, can be appreciated as an exemplary equation for the calculation. tan_d=(tan_green*dist_Bh_a+tan_blue*dist_Gh_a)/(dist_Bh_a+dist_Gh_a) (3) wherein tan_d denotes the tangent value of a correction angle D (an angular difference between the correction direction WP.sub.1 and the original direction WP.sub.0), dist_Bh_a denotes a length of the segment Bha and dist_Gh_a denotes a length of the segment Gha.), as well as a first distance value between the pixel to be adjusted and the white point (Fig. 5. Paragraph [0060]-LIU discloses a distance from the corrected color coordinate P.sub.1 to the white point W is WP.sub.1.); and
obtain adjusted coordinate information (Fig. 4-5. Paragraph [0029]-LIU discloses the corrected color direction and the corrected color coordinate P.sub.1for P.sub.0 can be calculated based on the two primary color direction deviations and the original color coordinate P.sub.0.) corresponding to the pixel to be adjusted in the original image (Fig. 4. Paragraph [0044]-LIU discloses assuming that a pixel has an original color coordinate P.sub.0 which is between the green direction WGh and the blue direction WBh.) based on the coordinate information of the white point (Fig. 4. Paragraph [0047]-LIU discloses the corrected color coordinate P1 can be further calculated using Equation (4) below with the correction angle D taken into account, i.e. the original color coordinate P.sub.0(u.sub.p0, v.sub.p0) is corrected to the coordinate P.sub.1(u.sub.p1, v.sub.p1) shown in FIG. 4. u.sub.p1=(u.sub.p0−u.sub.w)*cosD−(v.sub.p0−v.sub.w)*sinD+u.sub.w v.sub.p1=(v.sub.p0−v.sub.w)*cosD+(u.sub.p0−u.sub.w)*sinD+v.sub.w (4) wherein the white point W has a coordinate (u.sub.w, v.sub.w), D denotes the correction angle.), the first rotation angle value (Fig. 4. Paragraph [0051]-LIU discloses the correction angle D can be calculated based on the green direction deviation Dg.), the first angle value (Fig. 5, illustrates a first angle value between the pixel to be adjusted and the white point denoted by angle D. Paragraph [0045]-LIU discloses the mapping Equation (3) below can be used for calculating the offset, which, however, can be appreciated as an exemplary equation for the calculation. tan_d=(tan_green*dist_Bh_a+tan_blue*dist_Gh_a)/(dist_Bh_a+dist_Gh_a) (3) wherein tan_d denotes the tangent value of a correction angle D (an angular difference between the correction direction WP.sub.1 and the original direction WP.sub.0), dist_Bh_a denotes a length of the segment Bha and dist_Gh_a denotes a length of the segment Gha.) and the first distance value (Fig. 5. Paragraph [0059-0060]-LIU discloses the coordinate P.sub.1 can be mapped to the coordinate P.sub.2 in the color gamut BT.709 using a non-linear mapping algorithm. The mapping ratio can be calculated using the following method. First, a first compression parameterC.sub.1 is calculated. It is assumed that a distance from the white point W to a point a′ (u.sub.a′,v.sub.a′) on the boundary of the color gamut BT.2020 is Wa′, and a distance from the white point W to a point b′ (u.sub.b′,v.sub.b′) on the boundary of the color gamut BT.709 is Wb′, and a distance from the corrected color coordinate P.sub.1 to the white point W is WP.sub.1.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of OLSEN in view of ZHOU of an image correction method, comprising: obtaining an original image and a preset color adjustment strategy; obtaining pixel statistical information of the original image with the teachings of LIU of obtain coordinate information of a white point in u'v' space, coordinate information of a pixel to be adjusted in the original image, and a first rotation angle value of the pixel to be adjusted; obtain, based on the coordinate information of the white point and the coordinate information of the pixel to be adjusted, a first angle value between the pixel to be adjusted and the white point, as well as a first distance value between the pixel to be adjusted and the white point; and obtain adjusted coordinate information corresponding to the pixel to be adjusted in the original image based on the coordinate information of the white point, the first rotation angle value, the first angle value and the first distance value.
Wherein having OLSEN’s method for image color correction for the remediation of color blindness having obtain coordinate information of a white point in u'v' space, coordinate information of a pixel to be adjusted in the original image, and a first rotation angle value of the pixel to be adjusted; obtain, based on the coordinate information of the white point and the coordinate information of the pixel to be adjusted, a first angle value between the pixel to be adjusted and the white point, as well as a first distance value between the pixel to be adjusted and the white point; and obtain adjusted coordinate information corresponding to the pixel to be adjusted in the original image based on the coordinate information of the white point, the first rotation angle value, the first angle value and the first distance value.
The motivation behind the modification would have been to obtain a method for image color correction for the remediation of color blindness that reduces color confusion of a user and enhances the efficiency of the method. Since both OLSEN and LIU relate to image color correction in CIE color space, wherein OLSEN for modifying the color of individual pixels in a displayed image to reduce color confusion for users experiencing color blindness, while LIU to improve the conventional HDR to SDR conversion. Please see OLSEN et al. (US 20230016631 A1), Paragraph [0007], and LIU et al. (US 20210183029 A1), Paragraph [0004].
Claims 6 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over OLSEN et al. (US 20230016631 A1), hereinafter referenced as OLSEN, in view of ZHOU et al. (US 20230410380 A1), hereinafter referenced as ZHOU, and further in view of, HIRAKAWA (US 20150334267 A1), hereinafter referenced as HIRAKAWA.
Regarding claim 6, OLSEN in view of ZHOU explicitly teach the image correction method according to claim 1,
OLSEN further explicitly teaches wherein said obtaining the pixel statistical information of the original image comprises (Fig. 1A-1B. Paragraph [0045]-OLSEN discloses the method adjusts flagged pixel color information by translating (106) flagged pixel color coordinates (e.g., (x.sub.1, y.sub.1)) within the CIE color space to a second color coordinate (e.g., (x.sub.2, y.sub.2)) away from a confusion line (wherein pixel information is pixel statistical information).):
obtaining at least one of: coordinates and ranges of landing points of pixels of the original image in the Luv space (Fig. 5 and 6A. Paragraph [0067-0068]-OLSEN discloses the filter area 510 of FIG. 5 includes eight sub-divisions numerated from lowest x coordinate to largest, e.g., progressing to the right on the x axis of FIG. 5. The first and second x coordinates of f.sub.10(x) are equal, thereby defining f.sub.10(x) as a vertical line connecting coordinates of f.sub.9 and f.sub.1. The first sub-division x range begins with the lowest x coordinate, e.g., f.sub.10(x), f.sub.9(x), and f.sub.1(x) with further sub-divisions having higher x coordinates. As an example, the first sub-division can include the x coordinate range from 0.3 to 0.39, the second sub-division includes the x coordinate range from 0.4 to 0.49, etc. The system determines if a pixel color coordinate is within a sub-division by comparing the pixel x coordinate to the sub-division ranges (wherein a range of landing points is indicated by a sub-division range in the filter area).), or
a clustering result of the landing points of the pixels of the original image in the Luv space (Fig. 5 and 6A. Paragraph [0073]-OLSEN discloses the system determines that a pixel containing color information corresponding to color coordinate 612a (x.sub.1, y.sub.1) falls within filter area 610a and flags the pixel color coordinate 612a for adjustment (wherein a clustering result is a flagged pixel coordinate).).
OLSEN in view of ZHOU fail to explicitly teach a histogram of the original image in RGB space and a histogram of the original image in Luv space.
However, HIRAKAWA explicitly teaches a histogram of the original image in RGB space and a histogram of the original image in Luv space (Fig. 1. Paragraph [0055]-HIRAKAWA discloses the image feature values representing color can be a color histogram in a color space (RGB, HSV, L*a*b, L*u*v, etc.), for example.),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of OLSEN in view of ZHOU of an image correction method, comprising: obtaining an original image and a preset color adjustment strategy; obtaining pixel statistical information of the original image with the teachings of HIRAKAWA of a histogram of the original image in RGB space and a histogram of the original image in Luv space.
Wherein having OLSEN’s method for image color correction for the remediation of color blindness having a histogram of the original image in RGB space and a histogram of the original image in Luv space.
The motivation behind the modification would have been to obtain a method for image color correction for the remediation of color blindness that reduces color confusion of a user and enhances the efficiency of the method. Since both OLSEN and HIRAKAWA relate to color correction in images, wherein OLSEN for modifying the color of individual pixels in a displayed image to reduce color confusion for users experiencing color blindness, while HIRAKAWA the color tone changing from region to region in an image can be corrected with ease without the need of preparing a color chart for each region where the color tone changes due to factors such as the light source change. Please see OLSEN et al. (US 20230016631 A1), Paragraph [0007], and HIRAKAWA (US 20150334267 A1), Paragraph [0015].
Regarding claim 19, OLSEN in view of ZHOU explicitly teach the electronic device according to claim 14,
OLSEN further explicitly teaches wherein the at least one processor is further configured to perform the computer program to obtaining at least one of (Fig. 9. Paragraph [0107]-OLSEN discloses the processor 902 can process instructions for execution within the computing device 900, including instructions stored in the memory 904 or on the storage device 906 to display graphical information for a GUI on an external input/output device, such as a display 916 coupled to the high-speed interface 908.):
coordinates and ranges of landing points of pixels of the original image in the Luv space (Fig. 5 and 6A. Paragraph [0067-0068]-OLSEN discloses the filter area 510 of FIG. 5 includes eight sub-divisions numerated from lowest x coordinate to largest, e.g., progressing to the right on the x axis of FIG. 5. The first and second x coordinates of f.sub.10(x) are equal, thereby defining f.sub.10(x) as a vertical line connecting coordinates of f.sub.9 and f.sub.1. The first sub-division x range begins with the lowest x coordinate, e.g., f.sub.10(x), f.sub.9(x), and f.sub.1(x) with further sub-divisions having higher x coordinates. As an example, the first sub-division can include the x coordinate range from 0.3 to 0.39, the second sub-division includes the x coordinate range from 0.4 to 0.49, etc. The system determines if a pixel color coordinate is within a sub-division by comparing the pixel x coordinate to the sub-division ranges (wherein a range of landing points is indicated by a sub-division range in the filter area).), or
a clustering result of the landing points of the pixels of the original image in the Luv space (Fig. 5 and 6A. Paragraph [0073]-OLSEN discloses the system determines that a pixel containing color information corresponding to color coordinate 612a (x.sub.1, y.sub.1) falls within filter area 610a and flags the pixel color coordinate 612a for adjustment (wherein a clustering result is a flagged pixel coordinate).).
OLSEN in view of ZHOU fail to explicitly teach a histogram of the original image in RGB space and a histogram of the original image in Luv space.
However, HIRAKAWA explicitly teaches a histogram of the original image in RGB space and a histogram of the original image in Luv space (Fig. 1. Paragraph [0055]-HIRAKAWA discloses the image feature values representing color can be a color histogram in a color space (RGB, HSV, L*a*b, L*u*v, etc.), for example.),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of OLSEN in view of ZHOU of an image correction method, comprising: obtaining an original image and a preset color adjustment strategy; obtaining pixel statistical information of the original image with the teachings of HIRAKAWA of a histogram of the original image in RGB space and a histogram of the original image in Luv space.
Wherein having OLSEN’s method for image color correction for the remediation of color blindness having a histogram of the original image in RGB space and a histogram of the original image in Luv space.
The motivation behind the modification would have been to obtain a method for image color correction for the remediation of color blindness that reduces color confusion of a user and enhances the efficiency of the method. Since both OLSEN and HIRAKAWA relate to color correction in images, wherein OLSEN for modifying the color of individual pixels in a displayed image to reduce color confusion for users experiencing color blindness, while HIRAKAWA the color tone changing from region to region in an image can be corrected with ease without the need of preparing a color chart for each region where the color tone changes due to factors such as the light source change. Please see OLSEN et al. (US 20230016631 A1), Paragraph [0007], and HIRAKAWA (US 20150334267 A1), Paragraph [0015].
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant’s disclosure.
JONES et al. (US 20070091113 A1) - Systems and methods for processing data representative of a full color image. Such systems may comprise the steps of assisting a color blind person to indicate portions of an image which to their color-deficient vision are indistinguishable, and altering the image to cause those portions to become distinguisable and identifiable…Abstract, Fig. 12E-F.
MURABAYASHI et al. (US 20240202976 A1) – An information processing apparatus includes: a determiner configured to determine whether a combination of adjacent two colors in inputted image data is a combination in which a person with color blindness is likely to confuse the two colors; and a decider configured to decide, as a proposed change of the combination of the two colors, for the combination determined to be the combination in which the person with color blindness is likely to confuse the two colors by the determiner, a combination in which at least one of the two colors is changed such that the person with color blindness is capable of distinguishing the two colors and in which a degree of change of the at least one changed color of the two colors is minimized for a person with normal color vision…Abstract, Fig. 14.
IMAI et al. (US 20090060326 A1) – An objective color for a target color is set based on characteristic of the target color on a hue area to which the target color belongs in a color space represented by lightness, chroma and hue, and a shape of the most outer point of a color gamut reproducible by an output device on the hue area. A correction coefficient is calculated based on lightness, chroma and hue of the target color, lightness, chroma and hue of the objective color, a distance between the most outer point and the target color in the color space, and a distance between the most outer point and the objective color in the color space. A color correction quantity of each pixel of the image is calculated based on a distance between the target color and the objective color in the color space, a distance between the target color and a color of each pixel in the color space, the correction coefficient, and lightness and chroma of each pixel. The color of each pixel is corrected based on the color correction quantity.…Abstract, Fig. 4.
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/ETHAN N WOLFSON/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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