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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 04/20/2026 has been entered.
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 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.
Claim(s) 1-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Fujita (US 2017/0257584 A1).
Regarding Claim 1, Fujita teaches a method for processing image data provided by an image sensor (fig.1), the image data comprising an array of pixels (fig.2), the method comprising: a) determining the respective local brightness difference between a selected pixel and a set of pixels located adjacent to the respective pixel and assigned to the same color as the respective pixel (fig.3; Para.0042; determining high sensitivity pixels); and b) identifying the selected pixel as a defect pixel when the local brightness difference for the selected pixel exceeds an upper threshold value or is less than an lower threshold value (fig.3; Para.0042; defective correction unit 41; determining high sensitivity pixels and compare it to determine defective pixels.), and when the local brightness difference for the selected pixel exceeds a weighted maximum local brightness difference determined for the set of pixels located adjacent to the selected pixels and/or pixel or is less than a weighted minimum local brightness difference determined for the set of pixels located adjacent to the selected pixel (fig.5-7; brightness difference for the selected pixel to find the pixels of interest).
Regarding Claim 2, Fujita teaches the method according to claim 1, comprising calculating an average value for the set of pixels located adjacent to the selected pixel (Para.0055; average pixel values) in the step a) and determining the respecting local brightness difference for the selected pixel by calculating the difference between the value of the selected pixel and the calculated average value of the set of adjacent pixels (fig.5; Para.0063-65; calculating the difference between the pixel values).
Regarding Claim 3, Fujita teaches the method according to claim 2, wherein the average value is calculated as mean value, alpha-trimmed mean value or median value of the set of pixels surrounding the selected pixel and being assigned to the same color as the selected pixel (fig.5; Para.0063-65; calculating average value with surrounding pixels).
Regarding Claim 4, Fujita teaches the method according to claim 1, wherein the set of pixels considered used in step a) of determining the local brightness difference for a selected pixel are located in a window of a predetermined size, wherein the set of pixels are assigned to the same color as the selected pixel (fig.7; Para.0063-65; calculating the difference between the pixel values of same color B).
Regarding Claim 5, Fujita teaches the method according to claim 4, wherein the selected pixel for which the local brightness difference is determined, is located in the center of the window (fig.5; Para.0063-65; calculating high sensitivity for brightness difference).
Regarding Claim 6, Fujita teaches the method according to claim 1, comprising: determining the maximum local brightness difference of a set of pixels located adjacent to the selected pixel in a window of predetermined size, and identifying the selected pixel as a defective hot pixel when the local brightness difference exceeds the weighted maximum local brightness difference (fig.5; Para.0063-65; calculating the difference between the pixel values to find the defective pixels).
Regarding Claim 7, Fujita teaches the method according to claim 1, comprising: determining the minimum local brightness difference of a set of pixels located adjacent to the selected pixel in a window of predetermined size, and identifying the selected pixel as a defective cold pixel when the local brightness difference is less than the weighted minimum local brightness difference (fig.5; Para.0063-65; calculating the difference between the pixel values for brightness differences for defective pixels).
Regarding Claim 8, Fujita teaches the method according to claim 1, comprising: determining the second maximum local brightness difference for a set of pixels located adjacent to the selected pixel in a window of predetermined size and/or determining the second minimum local brightness difference for the set of pixels located adjacent to the selected pixel in a window of predetermine size, and identifying the selected pixel as a defective hot pixel when the local brightness difference exceeds the weighted second maximum local brightness difference and/or identifying the selected pixel as a defective cold pixel when the local brightness difference is less than the weighted second minimum local brightness difference (fig.5-7; Para.0063-65; calculating the difference between the pixel values for brightness differences for defective pixels).
Regarding Claim 9, Fujita teaches the method according to claim 8, comprising at least one of determining the second maximum local brightness difference for a set of pixels located adjacent to the selected pixel in a window of predetermined size from the local brightness difference values in the set having a positive value, or determining the second minimum local brightness difference for the set of pixels located adjacent to the selected pixel in a window of predetermine size from the local brightness difference values in the set having a positive value (fig.5-7; Para.0063-65; calculating the difference between the adjacent pixel values for brightness differences for defective pixels).
Regarding Claim 10, Fujita teaches the method according to claim 1, comprising at least one of i) adapting the at least one of upper threshold value and/or the lower threshold value considered used for identifying a selected pixel as a defective pixel, or ii) the weighting factors for the minimum and maximum local brightness difference by use of a neural network (fig.5-7; Para.0063-65; threshold value considered used for identifying a selected pixel as a defective pixel).
Regarding Claim 11, Fujita teaches the method according to claim 1, wherein the step a) of determining the respective local brightness difference for a selected pixel and step b) of identifying the selected pixel as defect pixel is carried out repeatedly by selecting each pixel of a pixel array provided by the image camera for an image and repeating the method for each selected pixel (fig.5; Para.0063-65; calculating the difference between the pixel values for the selective pixel as defective).
Regarding Claim 12, Fujita teaches the method according to claim 1, comprising correcting pixels identified as the defect pixel (fig.3).
Regarding Claim 13, Fujita teaches an image processor unit for processing image data provided by an image sensor, the image data comprising an array of pixels (fig.2-3; and 5), wherein the image processing unit is arranged to carry out the step. of the method according to claim 1.
Regarding Claim 14, Fujita teaches a non-transitory computer readable medium comprising a computer program including instructions which, when the program is executed by a processing unit, causes the processing unit to carry out the step. of the method of claim 1 (Para.0039; processing unit).
Regarding Claim 15, Fujita teaches the method according to claim 4, wherein the window of a predetermined size comprises one of a 4x4, 5x5 or 8x8 window (fig.6-7).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FAYEZ A BHUIYAN whose telephone number is (571)270-1562. The examiner can normally be reached on 9:00 - 6:00 M-F.
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, Lin Ye can be reached on 571-272-7372. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/FAYEZ BHUIYAN/
Examiner, Art Unit 2639
/LIN YE/Supervisory Patent Examiner, Art Unit 2638
Prosecution Insights