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 .
Specification
The disclosure is objected to because of the following informalities:
In [0084], the specification states, “if a predetermined condition in which luminance of the target pixel is greater than luminance of the neighboring pixels by a predetermined threshold or more is satisfied (Yes in S60), the gain selector 330 may determine LWBG to be the final gain (S50)”. Particularly, “the gain selector 330 may determine LWBG to be the final gain (S50)” should be corrected to “the gain selector 330 may determine CLWBG to be the final gain (S50)””
Appropriate correction is required.
Claim Rejections - 35 USC § 102
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)(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.
Claim(s) 1-5 and 16 are rejected under 35 U.S.C. 102(a)(2) as being unpatentable by Yu (US 20200228769 A1).
Regarding Claim 1, representative of Claim 16, Yu teaches an image signal processor comprising:
a local white balance gain (LWBG) calculator configured to calculate a first gain representing a ratio between red pixel data and green pixel data and a second gain representing a ratio between blue pixel data and green pixel data ([0064]: Ratio calculation unit 56 then calculates a ratio of the red and green pixel values (R/G) for each bin. Ratio calculation unit 56 also calculates a ratio of the blue and green pixel values (B/G) for each bin);
a local white balance gain (LWBG) corrector configured to generate a first correction gain and a second correction gain by filtering each of the first gain and the second gain ([0065]: chroma tint AWB unit 23 may then process the calculated ratios with homomorphic low-pass filter unit 57. Homomorphic low-pass filter unit 57 applies a homomorphic low-pass filter to the ratios to extract the chroma tint pattern. Homomorphic low-pass filtering may be useful for this application, as homomorphic filtering generally normalizes brightness across an image and increases contrast); and
a demosaicing corrector configured to correct each of the red pixel data, the green pixel data, and the blue pixel data using the first correction gain and the second correction gain ([abstract]: determining an illuminant under which the image was captured based on the determined chroma tint pattern, determining AWB parameters based at least in part on the determined illuminant, and applying the AWB parameters to the image. Examiner notes the chroma tint pattern is determined based in part on the filtered/correction ratios. The pattern is then used to determine the illuminant which is used to correct an image using the final determined AWB parameters).
Regarding Claim 2, Yu teaches the image signal processor according to claim 1. In addition, Yu teaches further comprising:
a demosaicing unit configured to generate the red pixel data, the green pixel data, and the blue pixel data by interpolating original image data corresponding to a predetermined color pattern ([0043] Bayer processing unit 32 may perform one or more initial processing techniques on the raw Bayer data received by image signal processor 6…Demosaic processing unit 34 may be configured to convert the processed Bayer image data into RGB values for each pixel of the image. See Fig. 2, auto white balancing (AWB) downstream of demosaicing).
Regarding Claim 3, Yu teaches the image signal processor according to claim 2. In addition, Yu teaches wherein:
the color pattern is a Bayer pattern ([0043] Bayer processing unit 32 may perform one or more initial processing techniques on the raw Bayer data received by image signal processor 6), a quad-Bayer pattern, or a nona-Bayer pattern.
Regarding Claim 4, Yu teaches the image signal processor according to claim 2. In addition, Yu teaches wherein:
the first gain and the second gain are calculated for the same target pixel ([0064]: Ratio calculation unit 56 then calculates a ratio of the red and green pixel values (R/G) for each bin. Ratio calculation unit 56 also calculates a ratio of the blue and green pixel values (B/G) for each bin).
Regarding Claim 5, Yu teaches the image signal processor according to claim 1, wherein the LWBG corrector is configured to:
perform smoothing-filtering on the first gain using an average and variance of first gains of pixels included in a filtering kernel ([0064]: Ratio calculation unit 56 then calculates a ratio of the red and green pixel values (R/G) for each bin. Ratio calculation unit 56 also calculates a ratio of the blue and green pixel values (B/G) for each bin, [0067] Low-pass filter 62 then filters out the high frequency components of the ratios in the frequency domain. Low-pass filter 62 may be any type of low-pass filter. One example is a Gaussian low-pass filter); and
perform smoothing filtering on the second gain using an average and variance of second gains of pixels included in the filtering kernel ([0064]: Ratio calculation unit 56 then calculates a ratio of the red and green pixel values (R/G) for each bin. Ratio calculation unit 56 also calculates a ratio of the blue and green pixel values (B/G) for each bin, [0067] Low-pass filter 62 then filters out the high frequency components of the ratios in the frequency domain. Low-pass filter 62 may be any type of low-pass filter. One example is a Gaussian low-pass filter).
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.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Yu (US 20200228769 A1) in view of Satpathy (S. Satpathy, M. C. Pradhan and S. Sharma, "Comparative Study of Noise Removal Algorithms for Denoising Medical Image Using LabVIEW," 2015 International Conference on Computational Intelligence and Communication Networks (CICN), Jabalpur, India, 2015, pp. 300-305, doi: 10.1109/CICN.2015.67).
Regarding Claim 6, Yu teaches the image signal processor according to claim 1. In addition, Yu teaches wherein the LWBG corrector is configured to:
perform [0064]: Ratio calculation unit 56 then calculates a ratio of the red and green pixel values (R/G) for each bin. Ratio calculation unit 56 also calculates a ratio of the blue and green pixel values (B/G) for each bin, [0067] Low-pass filter 62 then filters out the high frequency components of the ratios in the frequency domain. Low-pass filter 62 may be any type of low-pass filter. One example is a Gaussian low-pass filter).
Although, Yu teaches using Gaussian filtering on the ratios, Yu does not explicitly teach median filtering.
Satpathy teaches median filtering ([section II A]: many ways to denoise an image or a set of data…common approach is to use Gaussian filter, [Section II D]: the median filter is a nonlinear filtering technique, often used to remove noise. Such noise reduction is a typical preprocessing step to improve the results of later processing).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have modified Yu by the teachings of Satpathy by substituting Yu’s Gaussian filtering for Satpathy’s median filtering. Doing so would provide the predictable result of a filter for the ratios, reducing noise and thereby improving the accuracy of the ratios used in auto white balancing.
Allowable Subject Matter
Claims 7-15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JANICE VAZ whose telephone number is (703)756-4685. The examiner can normally be reached Monday-Friday 9:00-5:00pm.
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/JANICE E. VAZ/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667