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 required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) was filed with the application on 7/9/2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, 4, 5, 8, 9, 11, 13, and 17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Boulanger (US Patent Pub. # 2015/0358560).
As to claim 1, Boulanger discloses a method for detecting linear fixed pattern noise (FPN), the method comprising:
determining at least one portion of image data received from an image sensor (infrared sensors 132) as a region of interest (ROI) (8 nearest horizontal neighbors) (Para 166 and 277);
extracting a plurality of pixel values (d0-d3 on one side and d4-d7 on the other side) from a first row (horizontal neighbors) of the ROI (8 nearest horizontal neighbors) (Para 166 and 277);
calculating a brightness value (average result) of the first row (horizontal neighbors) based on the extracted pixel values (d0-d3 on one side and d4-d7 on the other side) (Para 166 and 277);
based on the calculated brightness value (average result), determining a first threshold (upper and lower threshold values may be used (thPix and −thPix)) related to a variance of the pixel values (d0-d3 on one side and d4-d7 on the other side) of the first row (horizontal neighbors), and determining a second threshold (predefined threshold) related to a difference (difference) between an average of the pixel values (average result) of the first row and an average of the pixel values (d0-d3 on one side and d4-d7 on the other side) of an adjacent row (adjacent row) to the first row (Para 166, 167, 277, 278, and 302-304);
calculating a first score (average result) indicating the variance (average) of the pixel values (d0-d3 on one side and d4-d7 on the other side) of the first row (Para 166 and 277);
calculating a second score (true mean difference) indicating a difference between the pixel value average (d0-d3 on one side and d4-d7 on the other side) of the first row and the pixel value average of the adjacent row (row j) to the first row (row i) (Para 304); and
determining whether the fixed pattern noise (fixed pattern noise (FPN)) is present in the first row (row i) based on the first score (average result) and the first threshold (thPix and −thPix) and the second score (true mean difference) and the second threshold (predefined threshold) (Para 166, 167, 277, 278, and 302-304).
As to claim 2, Boulanger teaches wherein a length in a first direction of the ROI (8 nearest horizontal neighbors) is smaller than a length in the first direction of the image data (arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) (Para 166 and 110); a length in a second direction perpendicular (column) to the first direction of the ROI (8 nearest horizontal neighbors) is equal to a length in the second direction (column correction terms) of the image data (arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) (Para 299); and the first direction is a row direction (row) of a subset of the image data(arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) (Para 166 and 110).
As to claim 4, Boulanger teaches wherein the calculating the second score (true mean difference) further includes: calculating the second score (true mean difference) of each of a second row (specific row) upwardly adjacent to the first row (adjacent rows) and a third row (adjacent rows) downwardly adjacent to the first row (specific row) (Para 302).
As to claim 5, Boulanger teaches wherein in response to the first row (specific row) being a first row of the image data, calculating only the second score (true mean difference) of the third row (adjacent rows); and in response to the first row (specific row) being a last row of the image data, calculating only the second score (true mean difference) of the second row (adjacent rows) (Para 302).
As to claim 8, Boulanger teaches further comprising: rotating the image data (arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) by 90 degrees before setting the portion of the image data as the ROI (8 nearest horizontal neighbors) (Para 301). Boulanger teaches the term “row” may be used to describe a row or a column, and likewise, the term “column” may be used to describe a row or a column, depending upon the application (Para 301).
As to claim 9, Boulanger discloses an image signal processor comprising:
processing circuitry (processor 195) configured to, process image data (image frames) received from an image sensor (infrared sensors 132) (Para 104 and 108);
detect whether fixed pattern noise (fixed pattern noise (FPN)) is present in each row (row)of the processed image data (image frames) (Para 157);
determine a portion of the received processed image data (image frames) as a region of interest (ROI) (8 nearest horizontal neighbors) (Para 166 and 277);
extract pixel values (d0-d3 on one side and d4-d7 on the other side) of each row of the ROI (8 nearest horizontal neighbors); calculate a brightness value (average result) of each row of the ROI based on the extracted pixel values (d0-d3 on one side and d4-d7 on the other side) (Para 166 and 277);
based on the calculated brightness value (average result), determine a first threshold (upper and lower threshold values may be used (thPix and −thPix)) related to a variance of the pixel values (d0-d3 on one side and d4-d7 on the other side) of each row (horizontal neighbors) of the ROI (8 nearest horizontal neighbors), and determine a second threshold (predefined threshold) related to a difference (difference) between an average of the pixel values (average result) of each row (horizontal neighbors) of the ROI (8 nearest horizontal neighbors) and an average of pixel values (d0-d3 on one side and d4-d7 on the other side) of an adjacent row (adjacent row)to each row (horizontal neighbors) of the ROI (8 nearest horizontal neighbors) (Para 166, 167, 277, 278, and 302-304);
calculate a first score (average result) indicating the variance (average) of the pixel values (d0-d3 on one side and d4-d7 on the other side) of each row (horizontal neighbors) of the ROI (8 nearest horizontal neighbors) (Para 166 and 277);
calculate a second score (true mean difference) indicating a difference between the average of the pixel values (d0-d3 on one side and d4-d7 on the other side) of each row (row i) of the ROI (8 nearest horizontal neighbors) and the average of the pixel values (d0-d3 on one side and d4-d7 on the other side) of the adjacent row (row j) thereto (Para 304); and
determine whether fixed pattern noise (fixed pattern noise (FPN)) is present in each row (horizontal neighbors) of the ROI (8 nearest horizontal neighbors) based on the first score (average result) and the first threshold (thPix and −thPix) and the second score (true mean difference) and the second threshold (predefined threshold) (Para 166, 167, 277, 278, and 302-304).
As to claim 11, Boulanger teaches wherein a length in a first direction of the ROI (8 nearest horizontal neighbors) is smaller than a length in the first direction of the image data (arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) (Para 166 and 110); a length in a second direction perpendicular (column) to the first direction of the ROI (8 nearest horizontal neighbors) is equal to a length in the second direction (column correction terms) of the image data (arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) (Para 299); and the first direction is a row direction (row) of a subset of the image data(arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) (Para 166 and 110).
As to claim 13, Boulanger teaches wherein the row adjacent (adjacent rows) to each row (specific row) of the ROI includes a row upwardly adjacent (adjacent rows) to each row (specific row) of the ROI and a row downward adjacent (adjacent rows) to each row (specific row) of the ROI; and the processing circuitry is further configured to, in response to a row (specific row) of the ROI being a first row of the image data, calculate only the second score (true mean difference) of the row downwardly adjacent (adjacent rows) to the row (specific row), and in response to the row (specific row) of the ROI being a last row (specific row) of the image data, calculate only the second score (true mean difference) of the row upwardly adjacent (adjacent rows) to the row (specific row) (Para 302).
As to claim 17, Boulanger teaches wherein the processing circuitry (195)is further comprising: rotating the image data (arrays of approximately 32 by 32 infrared sensors 132, approximately 64 by 64 infrared sensors 132, approximately 80 by 64 infrared sensors 132, or other array sizes may be used) by 90 degrees before setting the portion of the image data as the ROI (8 nearest horizontal neighbors) (Para 301). Boulanger teaches the term “row” may be used to describe a row or a column, and likewise, the term “column” may be used to describe a row or a column, depending upon the application (Para 301).
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 6, 14, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Boulanger (US Patent Pub. # 2015/0358560) in view of Olsson (US Patent Pub. # 2018/0063454).
As to claim 6, note the discussion above in regards to claim 1. Boulanger does not teach further comprising: in response to determining that the fixed pattern noise is present, displaying information indicating that the fixed pattern noise is present; and outputting the image data. Olsson teaches further comprising: in response to determining that the fixed pattern noise (fixed pattern noise correction image updater functional block FPN UPD 250) is present, displaying information indicating that the fixed pattern noise is present (zero (0)) (Para 113); and outputting (to display the received signal as a displayed image, e.g. to display a visual representation of an IR image or visual representation of IR image frames) the image data (Para 41). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have provided a fixed pattern noise correction image updater functional block FPN UPD as taught by Olsson to the infrared imaging module of Boulanger, to correct fixed pattern noise in thermal imaging (Para 2 of Olsson).
As to claim 14, Olsson teaches wherein the processing circuitry (processor 112) is further configured to: store a result matrix (fixed pattern noise correction image updater functional block FPN UPD 250) in memory, the result matrix (250) configured to store a detection result of the fixed pattern noise (fixed pattern noise); in response to a determination that the fixed pattern noise (fixed pattern noise) is present in each row of the ROI, recording a 1 (greater than zero (0)) in a corresponding row of the result matrix (250); and in response to a determination that the fixed pattern noise (fixed pattern noise) is absent in each row of the ROI, recording a 0 in the corresponding row of the result matrix (250) (Para 113).
As to claim 15, Olsson teaches wherein the processing circuitry (112) is further configured to: display information (to display the received signal as a displayed image, e.g. to display a visual representation of an IR image or visual representation of IR image frames) related to the fixed pattern noise (fixed pattern noise) based on the result matrix (250) (Para 41).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Boulanger (US Patent Pub. # 2015/0358560) in view of Shin (US Patent Pub. # 2021/0383555).
As to claim 10, note the discussion above in regards to claim 9. Boulanger does not teach wherein the processing circuitry is further configured to: perform at least one of color correction, auto white balance, gamma correction, color saturation correction, bad pixel correction, hue correction, or any combination thereof, on the image data received from the image sensor. Shin teaches wherein the processing circuitry (image signal processor 18) is further configured to: perform at least one of color correction (color correction), auto white balance (auto white balance), gamma correction (gamma correction), color saturation correction (color saturation correction), bad pixel correction (bad pixel correction), hue correction (hue correction), or any combination thereof, on the image data (signal output) received from the image sensor (one image sensor 14) (Para 41). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have provided an image signal processor as taught by Shin to the infrared imaging module of Boulanger, to provide an electronic device and a method for compensating crosstalk due to a height difference of filters in a multi-color filter array (Para 5 of Shin).
Allowable Subject Matter
Claims 3, 7, 12, and 16 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.
Claims 18-20 are allowed.
The following is an examiner’s statement of reasons for allowance:
As to independent claim 18 the combination of prior art references does not teach or fairly suggest the limitations cited within the claims. Independent claims 18 identify the uniquely distinct features "an image sensor including a pixel array, the pixel array including a plurality of pixels, each pixel of the plurality of pixels including a first photodiode and a second photodiode, the second photodiode having a larger light receiving area than a light receiving area of the first photodiode, wherein the pixel array is configured to, output a first pixel signal based on a first conversion gain using the second photodiode in a first illuminance range, output a second pixel signal based on a second conversion gain using the second photodiode in a second illuminance range, output a third pixel signal based on the first conversion gain using the first photodiode in a third illuminance range, and output a fourth pixel signal based on the second conversion gain using the first photodiode in a fourth illuminance range, wherein the first conversion gain is higher than the second conversion gain”.
It is noted that the closest prior art, Wang (US Patent Pub. # 2024/0283460) relates generally to image sensors, and in particular but not exclusively, relates to high dynamic range (HDR) complementary metal oxide semiconductor (CMOS) image sensors. Wang (US Patent Pub. # 2021/0218919) relates generally to digital image sensors. More particularly, embodiments relate to pixel-wise gain-adjusted digital conversion using programmable gain amplifiers (PGAs) in complementary metal-oxide semiconductor (CMOS) digital image sensors. Boulanger (US Patent Pub. # 2015/0358560) relate generally to infrared imaging devices and more particularly, for example, to systems and methods for multi-spectrum imaging using infrared imaging devices. However Wang, Wang, or Boulanger do not disclose an image sensor including a pixel array, the pixel array including a plurality of pixels, each pixel of the plurality of pixels including a first photodiode and a second photodiode, the second photodiode having a larger light receiving area than a light receiving area of the first photodiode, wherein the pixel array is configured to, output a first pixel signal based on a first conversion gain using the second photodiode in a first illuminance range, output a second pixel signal based on a second conversion gain using the second photodiode in a second illuminance range, output a third pixel signal based on the first conversion gain using the first photodiode in a third illuminance range, and output a fourth pixel signal based on the second conversion gain using the first photodiode in a fourth illuminance range, wherein the first conversion gain is higher than the second conversion gain. Therefore the application is allowable.
As to dependent claims 19 and 20, these claims depend on allowable independent claim 18.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
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/CHRISTOPHER K PETERSON/Primary Examiner, Art Unit 2637 3/17/2026