Prosecution Insights
Last updated: May 29, 2026
Application No. 18/444,492

IMAGE PROCESSING APPARATUS, TRAINING APPARATUS, IMAGE PROCESSING METHOD, TRAINING METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

Non-Final OA §102§103
Filed
Feb 16, 2024
Priority
Feb 22, 2023 — JP 2023-026043
Examiner
STREGE, JOHN B
Art Unit
2669
Tech Center
2600 — Communications
Assignee
Canon Kabushiki Kaisha
OA Round
1 (Non-Final)
87%
Grant Probability
Favorable
1-2
OA Rounds
7m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 87% — above average
87%
Career Allowance Rate
944 granted / 1087 resolved
+24.8% vs TC avg
Moderate +14% lift
Without
With
+14.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
12 currently pending
Career history
1099
Total Applications
across all art units

Statute-Specific Performance

§101
3.2%
-36.8% vs TC avg
§103
78.8%
+38.8% vs TC avg
§102
10.2%
-29.8% vs TC avg
§112
3.1%
-36.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1087 resolved cases

Office Action

§102 §103
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 . Election/Restrictions Claims 17-19, 21 and 23 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 01/20/26. 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)(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. Claims 1-7, 14-15, 20 and 22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ahn 2022/0180625. Regarding claim 1, Anh discloses an image processing apparatus (see paragraph 0002, computing device that performs a function of processing image quality of an input image) PNG media_image1.png 68 352 media_image1.png Greyscale , comprising: one or more processors; and one or more memories storing instructions executable by the one or more processors to cause the image processing apparatus to operate as: a feature extractor configured to extract an intermediate feature from an input image (see paragraph 0008, discloses a processor to execute instructions stored in memory to extract features of an input image, also see figure 7 step 710 paragraph 0138) PNG media_image2.png 226 336 media_image2.png Greyscale PNG media_image3.png 666 568 media_image3.png Greyscale PNG media_image4.png 48 338 media_image4.png Greyscale ; a map estimator configured to estimate an area map from the intermediate feature (see figure 7, step 730, an instance quality score map is obtained corresponding to each instance recognized [the instances have area thus the quality score map is interpreted as an area map) PNG media_image4.png 48 338 media_image4.png Greyscale ; a first image estimator configured to estimate a first image from the intermediate feature (see figure 7 step 740 where image quality processing is performed for each instance, and as seen in figure 4 the image quality processing goes through a first instance image quality processing module step 430, see paragraph 0107) PNG media_image5.png 490 730 media_image5.png Greyscale PNG media_image6.png 86 262 media_image6.png Greyscale ; a second image estimator configured to estimate a second image from the intermediate feature (see above figure 4 step 440 second image quality processing module) ; and an outputter configured to output an output image obtained by merging the first image and the second image based on the area map, wherein the second image estimator is trained to obtain predetermined image quality at a particular area based on the area map in the second image (see above figure 4 step 460 merging module which is based on the image quality map step 730 of figure 7). Regarding claim 2, Anh discloses the first image estimator estimates the first image obtained by applying first image processing to the input image, and the second image estimator estimates the second image obtained by applying second image processing different in characteristics from the first image processing to the input image (see step 740 of figure 7, perform image quality processing differently for each instance included in input image by using quality score corresponding to each instance included in input image). Regarding claim 3, Anh discloses the area map is a map that indicates whether an area is an area where an importance is placed on the first image processing or an area where an importance is placed on the second image processing (see paragraph 0051, a quality score [importance] is placed on each instance [area] to determine the image processing to be caried out) PNG media_image7.png 82 356 media_image7.png Greyscale Regarding claim 4, Anh discloses the outputter outputs the output image obtained by merging the first image and the second image at a ratio corresponding to a value indicated by the area map for each pixel (see paragraph 0125) PNG media_image8.png 64 352 media_image8.png Greyscale Regarding claim 5, the outputter outputs the output image generated by using the first image at the area where the importance is placed on the first image processing in the area map and by using the second image at the area where the importance is placed on the second image processing in the area map (see paragraph 0141) PNG media_image9.png 78 362 media_image9.png Greyscale . Regarding claim 6, the first image processing and the second image processing are noise reduction processing (see paragraph 0014) PNG media_image10.png 78 354 media_image10.png Greyscale Regarding claim 7, the first image is an image obtained through the noise reduction processing performed with an importance placed on image quality (see above paragraphs 0014 and 0125). Regarding claim 14, Anh discloses the input image includes a plurality of successive images timewise, the area map is a plurality of area maps corresponding to the plurality of images of the input image the first image is a plurality of first images corresponding to the plurality of images of the input image, and the second image is a plurality of second images corresponding to the plurality of images of the input image (see figure 14). PNG media_image11.png 520 560 media_image11.png Greyscale Regarding claim 15, Anh discloses a third image estimator configured to estimate a third image from the intermediate feature, wherein the outputter outputs the output image obtained by merging the first image, the second image, and the third image based on the area map, and the third image estimator is trained to obtain predetermined image quality at a particular area based on the area map in the third image (see 450 of figure 4 where a third image estimator is used and merged with the first and second). Claim 20 is similarly analyzed to claim 1. Claim 22 is similarly analyzed to claim 1. 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 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Anh. Regarding claim 10, as discussed above Anh discloses the limitations of claim 6. Anh does not explicitly disclose that the input image is an image degraded due to noise, however as Anh does mention noise suppression (see paragraph 0014) it is implied if not inherent that the input image would have noise. Thus it would be an obvious design choice to apply Anh to an input image that is degraded due to noise to suppress the noise and improve the output. Regarding claims 11-12, Anh does not explicitly disclose super-resolution processing for the first and second image processing, however does disclose that resolution conversion can be carried out with respect to the image data and focusing on image quality (see paragraph 0099, and 0014) PNG media_image12.png 78 344 media_image12.png Greyscale It is well known to use super-resolution processing to provide a high resolution image to which the Examiner declares official notice. As Anh discloses resolution conversion it would be obvious to use super-resolution with the motivation being to obtain a high quality image. Allowable Subject Matter Claim 8-9, 13, 16 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. Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN B STREGE whose telephone number is (571)272-7457. The examiner can normally be reached M-F 9-5 (PST). 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, Chan Park can be reached at (571)272-7409. 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. /JOHN B STREGE/Primary Examiner, Art Unit 2669
Read full office action

Prosecution Timeline

Feb 16, 2024
Application Filed
Feb 13, 2026
Non-Final Rejection mailed — §102, §103
May 12, 2026
Response Filed

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
87%
Grant Probability
99%
With Interview (+14.0%)
2y 11m (~7m remaining)
Median Time to Grant
Low
PTA Risk
Based on 1087 resolved cases by this examiner. Grant probability derived from career allowance rate.

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