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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 8/31/2026 has been entered.
Response to Arguments
Applicant's arguments filed 8/31/2026 have been fully considered but they are not persuasive.
Regarding Applicant’s arguments with respect to Tamama (page 8 of Remarks), in response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Regarding Applicant’s arguments with respect to Cui (page 8 of Remarks), in response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Regarding Applicant’s arguments with respect to Qiu (page 8 of Remarks), in response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
In view of the foregoing, the Examiner is not persuaded by Applicant’s arguments with respect to claim 1. Therefore, claim 1 stands rejected as further detailed below.
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.
Claims 1, 4-7 and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Tamama et al. (United States Patent Application Publication 2002/0135683), hereinafter referenced as Tamama, in view of Cui et al. (You Only Need 90K Parameters to Adapt Light: a Light Weight Transformer for Image Enhancement and Exposure Correction), hereinafter referenced as Cui, and further in view of Qui et al. (United States Patent Application Publication 2025/0247629), hereinafter referenced as Qui.
Regarding claim 1, Tamama discloses an image processing system, comprising: an image sensor that converts light into a raw image (figure 1a exhibits image sensor 150 as disclosed at paragraph 35); an image signal processor (ISP) that performs image processing on the raw image (figure 1 exhibits DSP subsystem 120 which performs all image processing as disclosed at paragraph 35). However, Tamama fails to disclose a predictor that dynamically generates correction parameters; and a plurality of adders that respectively add the correction parameters and corresponding base parameters, sums of which are as adjusted parameters to be dynamically fed to the ISP; wherein the correction parameters are dynamically generated prior to and for use within the ISP, and the adjusted parameters are dynamically fed to the ISP during the image processing to control operation of the ISP in raw-image domain.
Cui is a similar or analogous system to the claimed invention as evidenced Cui teaches an image processing system wherein the motivation of improving image quality would have prompted a predictable variation of Tamama by applying Cui’s known principal of providing a predictor that dynamically generates correction parameters (figure 3 shows a global prediction model which generates correction parameters); and a plurality of adders that respectively add the correction parameters and corresponding base parameters, sums of which are as adjusted parameters to be dynamically fed to the ISP (figure 3 shows that the parameters output by the GPM are added to default parameters to generate color matrix and gamma).
In view of the motivations such as improving image quality one of ordinary skill in the art would have implemented the claimed variation of the prior art system of Tamama.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
However, the Tamama in view of Cui fails to explicitly disclose wherein the correction parameters are dynamically generated prior to and for use within the ISP, and the adjusted parameters are dynamically fed to the ISP during the image processing to control operation of the ISP in raw-image domain.
Qui is a similar or analogous system to the claimed invention as evidenced Qui teaches an image processing method wherein the motivation of performing adaptive processing on images obtained by a camera in different scenarios would have prompted a predictable variation of Tamama in view of Cui by applying Qui’s known principal of wherein the correction parameters are dynamically generated prior to and for use within the ISP (figure 4 shows that ISP parameters are dynamically generated prior to and for use withing the ISP as disclosed at paragraph 135), and the adjusted parameters are dynamically fed to the ISP during the image processing to control operation of the ISP in raw-image domain (figure 4 further shows that the adjusted parameters are dynamically fed to the ISP to process the raw image as disclosed at paragraph 135), and wherein the predictor dynamically generates a plurality of module specific correction parameters (figure 3 shows a global prediction model which generates a plurality of correction parameters), and color correction, each correction parameter representing a residual relative to a corresponding base parameter (figure 3 shows that the parameters output by the GPM are added to default parameters to generate color matrix and gamma). When applying this known technique to Tamama which includes ISP modules for black level subtraction (figure 1c exhibits black clamping 310 as disclosed at paragraph 52), auto white balance (figure 1c which white balance device 316 as disclosed at paragraph 51), gamma correction (figure 1c exhibits gamma correction 320 as disclosed at paragraph 51) and color correction (figure 1x exhibits tone correction 332 which corrects color as disclosed at paragraph 99), it would have been obvious to a person having ordinary skill in the art before the effective filing date to applying Cui’s known technique of generating correction parameters for specific operations to each of the black level subtraction, auto white balance, gamma correction and color correction modules taught by Tamama such that the combination teaches wherein the predictor dynamically generates a plurality of module specific correction parameters respectively corresponding to black level subtraction, auto white balance, gamma correction, and color correction.
In view of the motivations such as performing adaptive processing on images obtained by a camera in different scenarios one of ordinary skill in the art would have implemented the claimed variation of the prior art system of Tamama in view of Cui.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
However, the Tamama in view of Cui fails to explicitly disclose wherein the correction parameters are dynamically generated prior to and for use within the ISP, and the adjusted parameters are dynamically fed to the ISP during the image processing to control operation of the ISP in raw-image domain, and each adjusted parameter is fed to a corresponding ISP module to independently control operation of that module.
Qui is a similar or analogous system to the claimed invention as evidenced Qui teaches an image processing method wherein the motivation of performing adaptive processing on images obtained by a camera in different scenarios would have prompted a predictable variation of Tamama in view of Cui by applying Qui’s known principal of wherein the correction parameters are dynamically generated prior to and for use within the ISP (figure 4 shows that ISP parameters are dynamically generated prior to and for use withing the ISP as disclosed at paragraph 135), and the adjusted parameters are dynamically fed to the ISP during the image processing to control operation of the ISP in raw-image domain (figure 4 further shows that the adjusted parameters are dynamically fed to the ISP to process the raw image as disclosed at paragraph 135). When applying this known technique to Tamama in view of Cui in which Tamama uses a plurality of modules to perform image processing, it would have been obvious to a person having ordinary skill in the art that each of the parameters would be fed to their corresponding module in order to control that module using the updated parameters such that the combination teaches wherein each adjusted parameter is fed to a corresponding ISP module to independently control operation of that module.
In view of the motivations such as performing adaptive processing on images obtained by a camera in different scenarios one of ordinary skill in the art would have implemented the claimed variation of the prior art system of Tamama in view of Cui.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Regarding claim 4, Tamama in view of Cui and further in view of Qui discloses the system of claim 1, in addition, Tamama discloses a demosaic device that reconstructs a full-color image from incomplete color samples from the image sensor (figure 1c exhibits CFA interpolation 330 which generates a full color image as disclosed at paragraph 96).
Regarding claim 5, Tamama in view of Cui and further in view of Qui discloses the system of claim 4, in addition, Tamama discloses wherein the ISP further comprises: a black level subtraction (BLS) device that corrects a black level of the image according to a BLS adjusted parameter (figure 1c exhibits black clamping 310 as disclosed at paragraph 52); an auto white balance (AWB) device that adjusts colors in an image represented by the raw image according to an AWB adjusted parameter (figure 1c which white balance device 316 as disclosed at paragraph 51); a gamma correction (GC) device that performs a nonlinear operation to adjust luminance of the image represented by the raw image according to a GC adjusted parameter (figure 1c exhibits gamma correction 320 as disclosed at paragraph 51); and a color correction (CC) device that adjusts colors in the image represented by the raw image according to a CC adjusted parameter (figure 1x exhibits tone correction 332 which corrects color as disclosed at paragraph 99). Furthermore, it would have been obvious to adjust each of these functions using the prediction taught by Cui as discussed above with respect to claim 1 in order to image each process to provide a better corrected and higher quality image.
Regarding claim 6, Tamama in view of Cui and further in view of Qui discloses the system of claim 5, in addition, Tamama discloses wherein the BLS device receives the raw image, the AWB device receives an output from the BLS device, the GC device receives an output from the AWB device, the demosaic device receives an output from the GC device, and the CC device receives an output from the demosaic device (figure 1c shows that the process starts with black level correction which receives RAW data from the ADC at 310, the RAW data processed by black correction is then received by the white balance correction 316, the white balance corrected data is provided for gamma correction at 320 the output of which is provided to the CFA interpolator for demosaicing at 330 and finally the demosaiced data is color corrected at 332).
Regarding claim 7, Tamama in view of Cui and further in view of Qui discloses the system of claim 5, in addition, however, Tamama fails to disclose wherein the predictor generates a BLS correction parameter, an AWB correction parameter, a GC correction parameter and a CC parameter, which are respectively added to a BLS base parameter, an AWB base parameter, a GC base parameter and a CC base parameter, thereby resulting in a BLS adjusted parameter, an AWB adjusted parameter, a GC adjusted parameter and a CC adjusted parameter for the BLS device, the AWB device, the GC device and the CC device respectively.
Cui is a similar or analogous system to the claimed invention as evidenced Cui teaches an image processing system wherein the motivation of improving image quality would have prompted a predictable variation of Tamama by applying Cui’s known principal of providing a predictor that dynamically generates correction parameters (figure 3 shows a global prediction model which generates correction parameters); and a plurality of adders that respectively add the correction parameters and corresponding base parameters, sums of which are as adjusted parameters to be dynamically fed to the ISP (figure 3 shows that the parameters output by the GPM are added to default parameters to generate color matrix and gamma). When applying this known technique to Tamama which corrects black level, white balance, gamma and color, it would have been obvious to create a predictor which generates a BLS correction parameter, an AWB correction parameter, a GC correction parameter and a CC parameter, which are respectively added to a BLS base parameter, an AWB base parameter, a GC base parameter and a CC base parameter, thereby resulting in a BLS adjusted parameter, an AWB adjusted parameter, a GC adjusted parameter and a CC adjusted parameter for the BLS device, the AWB device, the GC device and the CC device respectively in order to improve the quality of each of the corrections performed by Tamama.
In view of the motivations such as improving image quality one of ordinary skill in the art would have implemented the claimed variation of the prior art system of Tamama.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Regarding claim 9, Tamama in view of Cui and further in view of Qui discloses the system of claim 5, in addition, Tamama discloses wherein the image sensor is overlaid with a color filter array (figure 7a shows that a Bayer color filter is overlaid on the sensor).
Regarding claim 10, Tamama in view of Cui and further in view of Qui discloses the system of claim 9, in addition, Tamama discloses wherein the color filter array comprises a Bayer filter (figure 7a shows that a Bayer color filter is overlaid on the sensor).
Regarding claim 11, Tamama in view of Cui and further in view of Qui discloses the system of claim 1, in addition, Cui discloses wherein the predictor comprises: a feature encoder that extracts features from the raw image (page 6 paragraph 3 teaches “we first stack two convolutions as a lightweight encoder, which encodes the features in a high dimension with lower resolution”); a position embedding device that adopts depth-wise convolution to reduce computational complexity (figure 3 shows 3x3 DWConv that embeds features at positions); a cross-attention device that performs cross-attention with global queries, each of which represents a parameter to be predicted (figure 3 exhibits a cross attention device with is the second block which uses K, V and Q values, where Q is a global query as discussed at page 6 paragraph 3 “our global component queries Q are initialised as zeros without extra multi-head self-attention. Q is global component learn able embedding that attends keys K and values V generated from encoded features”); and a feedforward device that decodes the features and reduces dimensions thereof, thereby resulting in the correction parameters (figure 3 exhibits a third block which is a feedforward device that outputs correction parameters as discussed at page 6 paragraph 3 “After feed forward network (FFN) [18] with two linear layers, we add two extra parameters with special initialisation to output colour matrix and gamma”).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Tamama in view of Cui in view of Qui and further in view of Zhang et al. (United States Patent Application Publication 2024/0305782), hereinafter referenced as Zhang.
Regarding claim 2, Tamama in view of Cui and further in view of Qui discloses the system of claim 1, in addition, Cui discloses a converter that packs same color signals of the raw image to result in a packed image, which is fed to the predictor before generating the correction parameters.
Zhang is a similar or analogous system to the claimed invention as evidenced Zhang teaches a method for image processing wherein the motivation of separating color information to the greatest extent thereby improving processing accuracy would have prompted a predictable variation of Tamama by applying Zhang’s known principal of packing same color signals of the raw image to result in a packed image, which is output before being processed (paragraph 146 teaches converting a RAW imaging into a multi-channel image with each channel having a reduced size compared to the RAW image).
In view of the motivations such as separating color information to the greatest extent thereby improving processing accuracy one of ordinary skill in the art would have implemented the claimed variation of the prior art system of Cui.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Tamama in view of Cui in view of Qui in view of Zhang and further in view of Ge (Chinese Patent Publication 118799172). Note that all text citations refer to the attached machine translation.
Regarding claim 3, Tamama in view of Cui in view of Qui and further in view of Zhang discloses the system of claim 2, however, Tamama fails to disclose discloses wherein the converter packs the color signals of the raw image into BGGR format, where B represents blue color, G represents green color and R represent red color.
Tamama in view of Cui and further in view of Zhang teaches data packed in to a RGGB format (paragraph 147 of Zhang). Ge teaches that a packed format may be BGGR (paragraph 37). Because both Tamama in view of Cui and further in view of Zhang and Ge teach packed image formats, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to substitute the BGGR format taught by Ge for the RGGB format taught by Tamama in view of Cui and further in view of Zhang to achieve the predictable result of packing an image into reduced size color channels for processing.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Tamama in view of Cui in view of Qui and further in view of Adamski et al. (United States Patent Application Publication 2024/0346805), hereinafter referenced as Adamski.
Regarding claim 8, Tamama in view of Cui and further in view of Qui discloses the system of claim 5, in addition, Tamama discloses wherein the BLS adjusted parameter comprises a black level offset defining a value to be subtracted from each pixel (paragraph 65 teaches that black clamping subtracts an offset from each pixel), the AWB adjusted parameter comprises gains respectively applied to red, green and blue channels (figure 8 shows that white balance is a gain applied to the color channels), the GC adjusted parameter comprises a gamma value that is an exponent in power-law expression used for gamma correction, and the CC adjusted parameter comprises a color correction matrix used to transform colors (paragraph 99 teaches the color correction parameters are a color correction matrix).
Tamama teaches using a lookup table for gamma correction (paragraph 91). Adamski teaches performing gamma correction using a gamma value which is an exponent of a power law function (paragraph 20). Because both Tamama and Adamski teach methods for performing gamma correction, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to substitute the power law function taught by Adamski for the lookup taught by Tamama to achieve the predictable result of performing gamma correction on an image.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Conclusion
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JASON A. FLOHRE
Patent Examiner
Art Unit 2637
/JASON A FLOHRE/Patent Examiner, Art Unit 2637
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