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 .
Response to Arguments
Applicant’s arguments/amendment filed on 12/10/2025 have been entered and made of record.
Applicant's arguments filed 12/30/2025 with respect to 35 U.S.C. 102 and Tamura have been fully considered but they are not persuasive.
Applicant argues
Tamura does not appear to discuss separately processing different pixels in a filter kernel based on the pixel's image color such as from an image sensor, as is described in the pending claims. More specifically, the claims as amended now each recite limitations such as claim 1’s "a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region having a same pixel color and within a same region of the filter kernel," which are not present in Tamura. Such amendments are supported at least by paragraphs 69 and 70 of the specification as filed, and can be easily visualized with reference to the example of Figure 7B of the pending application
The examiner disagrees, the examiner notes in paragraph 40 : “The processing explained here is performed independently for each of the three signals of RGB, but here, for simplification of explanation, a specific one color, for example, red is explained as an example.” Note that the filtering is performed independently for each color and therefore all the pixels will be of one color plane e.g. red when filtering is performed.
Applicant's arguments filed 12/30/2025 with respect to 35 U.S.C. 102 and Rhee have been fully considered but they are not persuasive.
Applicant argues:
“Rhee appears to discuss generally "techniques for optimizing convolution filters," in which "embodiments may determine, based on an analysis of a plurality of values of a convolution filter, an optimization operation to optimize at least one value of the plurality of values of the convolution filter" (the Abstract).
The cited portions of Rhee appear to discuss how optimizing a convolution filter such that the "filter weights have lower variance and/or increased occurrences of zero values as filter weights," and such that "the optimized convolution filters may have increased numbers of identical non-zero weight values" (paragraph 12).
Rhee again does not appear to discuss limitations such as amended claim 1 "a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region having a same pixel color and within a same region of the filter kernel," and so does not anticipate the claims as amended.”
The examiner notes that Rhee discloses “a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region within a same region of the filter kernel,” as discussed in the rejection below. Rhee uses a window do define a region for the filtering in for example paragraph 28. The convolution is applied to pixel in the window i.e. the same region. The examiner agrees however that the language is “having a same pixel color” is not taught by Rhee. This feature is discussed in the new grounds of rejection below.
Applicant's arguments filed 12/30/2025 with respect to 35 U.S.C. 101 have been fully considered but they are not persuasive.
Applicant argues:
Applicant has amended the independent claims 1, 15, and 21 to reflect features such as "thereby providing a filtered output image", further evidencing a practical application that is more than an abstract idea. These amendments are supported by the specification as filed, which discusses in paragraph 35, for example, that "image signals 102 may be processed, thereby generating output signals 106" and in paragraph 33, that "averaging coefficients of a kernel may improve robustness and performance of such a kernel for denoising applications as well as reducing a number of delayed lines in streaming processing."
Applicant believes that the amended claims now more clearly recite processes that recite a practical application with a concrete, useful, tangible result, and that therefore comprise significantly more than an abstract idea in that they provide such a practical application. The pending claims also more clearly result in demonstrated improvements to the efficiency of a technology as explained more fully below, and so these claims are believed to be patent-eligible under 35 U.S.C. §101.
More specifically, applicant notes that the pending claims integrate any abstract idea
present into a practical application, and so are patent-eligible under §101. John Squires, Director of the USPTO in a December 4, 2025 memorandum distributed to examiners, discussed an Appeals Review Panel decision on In re Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) vacating a PTAB§101 rejection PTAB rejection was vacated because "the claims were directed to training a machine learning model on multiple tasks, while preserving prior tasks performed, which properly integrated an otherwise abstract idea into a practical application." The pending claims, as amended, provide a filtered output image, which comprises a clear practical application much as in In re DesJardins.
The pending claims in the present case are also directed to improvement in the
functioning of a specific technical machine and/or process, and provide an improvement to technology much as in In re DesJardins. More specifically, the application as filed discusses how "averaging coefficients of a kernel may improve robustness and performance of such a kernel for denoising applications as well as reducing a number of delayed lines in streaming" (paragraph 33), and how "Examples described herein relate to improving efficiency with which an image processing system performs convolution operations by reducing a number of multipliers and an amount of storage space required to generate an output signal data value" (paragraph 38), thereby significantly improving the performance of image filtering systems that employ the methods and systems described and claimed.
In Deputy Commissioner Charles Kim's memorandum of August 4th, he notes that improvements to a technical field or technology are present where a "claim reflects an improvement to the functioning of a computer or to another technology or technical field, integrating a recited judicial exception into a practical application of the exception" and that "whether a claim improves technology or a technical field is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome.''
The pending claims here recite a particular solution to improving the efficiency of
filtering image data. More specifically, the claimed "same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region having a same pixel color and within a same region of the filter kernel" and "convolving image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame, thereby providing a filtered output image" comprises a particular wav toachieve the desired outcome, and represents a measurable improvement to the functioning of a computer or a technologv.
The improvement provided therefore resides in the performance of a particular machine or process, much as in In re DesJardins, in that it provides an improvement to the efficiency of image processing. This amounts to a practical application, just as in In re DesJardins, and is therefore patent eligible under 101.
The pending claims as amended therefore now are not merely abstract ideas as they integrate any abstract idea present into a practical application and they reflect an improvement to the functioning of a computer or to another technology or technical field. The claims are therefore significantly more than an abstract idea under .101, and reexamination and withdrawal of this rejection is therefore respectfully requested.
Applicants note that guidance regarding §101 eligibility changes rapidly, and that different art units or examiners may look for different indications of subject matter eligibility. Applicants invite any examiner proposed amendments, interview, or the like that may facilitate prosecution and allowance of these pending claims.
The examiner disagrees that this case is similar to Ex Parte DesJardins; Ex parte DesJardins was directed to a detailed method of training a neural network to overcome a problem of “catastrophic forgetting”. Here the claims are merely directed to a mathematical algorithm for speeding up convolution performed on an image. See MPEP 2106.04(a)(2):
The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. The Supreme Court has identified a number of concepts falling within this grouping as abstract ideas including: a procedure for converting binary-coded decimal numerals into pure binary form, Gottschalk v. Benson, 409 U.S. 63, 65, 175 USPQ2d 673, 674 (1972); a mathematical formula for calculating an alarm limit, Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ2d 193, 195 (1978); the Arrhenius equation, Diamond v. Diehr, 450 U.S. 175, 191, 209 USPQ 1, 15 (1981); and a mathematical formula for hedging, Bilski v. Kappos, 561 U.S. 593, 611, 95 USPQ 2d 1001, 1004 (2010). [AltContent: rect]
The Court’s rationale for identifying these "mathematical concepts" as judicial exceptions is that a ‘‘mathematical formula as such is not accorded the protection of our patent laws,’’ Diehr, 450 U.S. at 191, 209 USPQ at 15 (citing Benson, 409 U.S. 63, 175 USPQ 673), and thus ‘‘the discovery of [a mathematical formula] cannot support a patent unless there is some other inventive concept in its application.’’ Flook, 437 U.S. at 594, 198 USPQ at 199. In the past, the Supreme Court sometimes described mathematical concepts as laws of nature, and at other times described these concepts as judicial exceptions without specifying a particular type of exception. See, e.g., Benson, 409 U.S. at 65, 175 USPQ2d at 674; Flook, 437 U.S. at 589, 198 USPQ2d at 197; Mackay Radio & Telegraph Co. v. Radio Corp. of Am., 306 U.S. 86, 94, 40 USPQ 199, 202 (1939) (‘‘[A] scientific truth, or the mathematical expression of it, is not patentable invention[.]’’). More recent opinions of the Supreme Court, however, have affirmatively characterized mathematical relationships and formulas as abstract ideas. See, e.g., Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 218, 110 USPQ2d 1976, 1981 (2014) (describing Flook as holding "that a mathematical formula for computing ‘alarm limits’ in a catalytic conversion process was also a patent-ineligible abstract idea."); Bilski v. Kappos, 561 U.S. 593, 611-12, 95 USPQ2d 1001, 1010 (2010) (noting that the claimed "concept of hedging, described in claim 1 and reduced to a mathematical formula in claim 4, is an unpatentable abstract idea,").
The examiner believes the facts of this case are more similar to Gottschalk v. Benson, 409 U.S. 63, 65, 175 USPQ2d 673, 674 (1972); or Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ2d 193, 195 (1978). The claim elements here are directed to a mathematical process for performing the mathematical function of convolution. The elements are not applied to any particular image processing function or image filtering function but rather to merely convolution on images in general. There are no additional element beyond the abstract idea in claims 1-20 as such there are no additional elements for integration into a practical application or to provide significantly more. Claim 21 one has generic computer components as additional elements. As the claims are not integrated into a practical application or nor do they provide significantly more.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Re claim 1 The claim recites “ A method comprising: convolving image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame, thereby providing a filtered output image wherein: kernel coefficients comprising part of a filter kernel to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame are selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region having a same pixel color and within a same region of the filter kernel.”
The examiner notes that “A method comprising: convolving image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame, thereby providing a filtered output image” directed to a method of convolving an image with a filter kernel to produce an output. Convolution is a mathematical operation and the method merely describes mathematical techniques for performing convolution faster. This fits within the mathematical concepts grouping of abstract idea.
The examiner notes that the elements “wherein: kernel coefficients comprising part of a filter kernel to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame are selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region having a same pixel color and within a same region of the filter kernel.” Merely further define the algorithm for performing convolution; convolution is a mathematical operation and the method merely describes mathematical techniques for performing convolution faster. This fits within the mathematical concepts grouping of abstract idea.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 2 The additional elements of claim 2 “wherein: pixel locations in the first region are mapped to the same coefficient value of the set of coefficient values based, at least in part, on full-granularity coefficient values computed for the pixel locations in the first region” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 3 The additional elements of claim 3 “wherein the same coefficient value is computed based, at least in part, on full-granularity coefficient values including at least some of the full-granularity coefficient values computed for the pixel locations.” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 4 The additional elements of the claim “wherein the same coefficient value is computed as an average of the full-granularity coefficient values” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 5 The additional elements of the claim “wherein the pixel locations in the first region are mapped to the same coefficient value based, at least in part, on an association of the full-granularity coefficient values with a range of values including the same coefficient value” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 6 The additional elements of the claim “wherein: the same coefficient value is selected to be applied to the image signal intensity values of the multiple pixel locations based, at least in part, a location of the first region relative to the output pixel location” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 7 The additional elements of the claim “wherein the first region is peripheral to a second region the at least a portion of pixel locations in the image frame, the second region containing the output pixel location” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 8 The additional elements of the claim “wherein: the first region is at a vertical periphery to the second region; a single kernel coefficient is applied to image signal intensity values of multiple pixel locations in the first region extending in a vertical direction; and kernel coefficients are applied with full granularity in a horizontal dimension” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 9 The additional elements of the claim “wherein: the first region is at a lateral periphery to the second region; a single kernel coefficient is applied to image signal intensity values of multiple pixel locations in the first region extending in a horizontal direction; and kernel coefficients are applied with full granularity in a vertical dimension” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 10 The additional elements of the claim “wherein convolving image signal intensity values associated with pixel locations in the first region comprises: summing image signal intensity values associated with two or more pixel locations in the first region; multiplying the summed image signal intensity values by the same coefficient value to compute a product; and determining the output image signal intensity value based, at least in part, on the computed product” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 11 The additional elements of the claim “further comprising: mapping image signal intensity values for at least some pixel locations in a second region of the image frame to a single image signal intensity value; multiplying the single image signal intensity value by a coefficient value selected from the set of coefficient values to compute a product; and determining the output image signal intensity value based, at least in part on the computed product” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 12 The additional elements of the claim “wherein mapping the image signal intensity values comprises averaging the image signal intensity values” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 13 The additional elements of the claim “further comprising: selecting between and/or among multiple modes to convolve the image signal intensity values associated with the at least a portion of pixel locations in the image frame, the multiple modes to convolve including at least a first mode comprising application of the same coefficient value to image signal intensity values of the multiple pixel locations in the first region” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 14
The additional elements of the claim “wherein the same coefficient value is selected to be a reduced granularity coefficient value or a reduced precision value based, at least in part, on a location of the first region relative to the output pixel location” merely further define the mathematical concept of performing the convolution.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 15 The claim recites “ A method comprising: mapping original image signal intensity values of a plurality of pixel locations in a portion of an image frame to a single image signal intensity value to be representative of the pixel locations in an augmented portion of the image frame; and convolving image signal intensity values associated with the plurality of pixel locations in the augmented portion of the image frame by applying one or more kernel coefficients comprising part of a filter kernel to the single image signal intensity value; the single image signal intensity value corresponding to original signal intensity values within a same region of the filter kernel and having a same pixel color.”
The examiner notes that “mapping original image signal intensity values of a plurality of pixel locations in a portion of an image frame to a single image signal intensity value to be representative of the pixel locations in an augmented portion of the image frame” is merely a part an algorithm for mapping coefficients in a kernel to a single value in preparation for convolution in the next portion of the claim. Convolution is a mathematical operation and the method merely describes mathematical techniques for performing convolution faster. This fits within the mathematical concepts grouping of abstract idea.
The examiner notes that “convolving image signal intensity values associated with the plurality of pixel locations in the augmented portion of the image frame by applying one or more kernel coefficients comprising part of a filter kernel to the single image signal intensity value; the single image signal intensity value corresponding to original signal intensity values within a same region of the filter kernel and having a same pixel color” is directed to a method of convolving an image with a filter kernel by mapping image elements to intensity values. Convolution is a mathematical operation and the method merely describes mathematical techniques for performing convolution faster. This fits within the mathematical concepts grouping of abstract idea.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 16
The additional elements of the claim “further comprising determining the single image signal intensity value based, at least in part, on an average of the original image signal intensity values” merely further define the mathematical concept of performing the convolution and mapping.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 17
The additional elements of the claim “determining the single image signal intensity value based, at least in part, on selection of a representative image signal intensity value from among the original image signal intensity values” merely further define the mathematical concept of performing the convolution and mapping.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 18
The additional elements of the claim “wherein: kernel coefficients to be applied to image signal intensity values for pixels in the augmented portion of the image frame are selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the augmented portion of the image frame” merely further define the mathematical concept of performing the convolution and mapping.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 19
The additional elements of the claim “wherein: the image frame comprises a multi-color channel image frame; and the plurality of pixel locations in the augmented portion of the image frame are dis-contiguous and associated with a same color channel” merely further define the mathematical concept of performing the convolution and mapping.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 20
The additional elements of the claim “wherein the original image signal intensity values of the plurality of pixel locations are mapped to the single image intensity value and the one or more kernel coefficients are applied to the single image signal intensity value responsive to a mode configured at runtime” merely further define the mathematical concept of performing the convolution and mapping.
The claim does not recite additional elements that integrate the abstract idea into a practical application or amount to significantly more than what is well known routine and conventional in the art because the claim does not recite an additional element. Therefore, the claim is directed to an abstract idea without significantly more.
Re claim 21 The claim recites “convolve image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame wherein: kernel coefficients comprising part of a filter kernel to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame to be selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region having a same pixel color and within a same region of the filter kernel.”
The examiner notes that “convolve image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame,” directed to a method of convolving an image with a filter kernel to produce an output. Convolution is a mathematical operation and the method merely describes mathematical techniques for performing convolution faster. This fits within the mathematical concepts grouping of abstract idea.
The examiner notes that the elements “wherein: kernel coefficients comprising part of a filter kernel to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame to be selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region having a same pixel color and within a same region of the filter kernel.” Merely further define the algorithm for performing convolution; convolution is a mathematical operation and the method merely describes mathematical techniques for performing convolution faster. This fits within the mathematical concepts grouping of abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim
only recites additional elements – using a processor and a memory to perform the mathematical concept. The processor and memory are recited at a high-level of generality (i.e., as a generic processor and memory performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly
more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a processor and memory to perform the mathematical concept amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
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.
Claim(s) 1-3, 6, 7, 10-18 20 and 21 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tamura US 2019/0050967.
Re claim 1 Tamura discloses
A method comprising:
convolving image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame, (see paragraph 50 note that a input pixel value is convolved with a filter to get and output pixel) there by providing a filter output image (see paragraph 50 and abstract and paragraph 63 note that note that smoothing is performed for each pixel to produce a noise reduced image )wherein:
kernel coefficients comprising part of a filter kernel to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame are selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region (see paragraph 53 note some of the filter coefficients for the filter window are selected to have the same value those pixels are summed) having a same pixel color (see paragraph 40 “The processing explained here is performed independently for each of the three signals of RGB, but here, for simplification of explanation, a specific one color, for example, red is explained as an example.” Note that the filtering is performed independently for each color and therefore all the pixels will be of one-color plane e.g. red) and within a same region of the filter kernel (see paragraph 53 note that the same filter coefficients belong to the filter window corresponding to the region).
Re claim 2 Tamura discloses pixel locations in the first region are mapped to the same coefficient value of the set of coefficient values based, at least in part, on full- granularity coefficient values computed for the pixel locations in the first region (see paragraph 51 table 1 note that the gaussian filter kernel has a weight for each pixel in the window and as such is full granularity see paragraph 53 note that same coefficients are determined from the gaussian window).
Re claim 3 Tamura discloses wherein the same coefficient value is computed based, at least in part, on full-granularity coefficient values including at least some of the full-granularity coefficient values computed for the pixel locations. (see paragraph 51 table 1 note that the gaussian filter kernel has a weight for each pixel in the window and as such is full granularity see paragraph 53 note that same coefficients are determined from the gaussian window).
Re claim 6 Tamura discloses the same coefficient value is selected to be applied to the image signal intensity values of the multiple pixel locations based, at least in part, a location of the first region relative to the output pixel location (see paragraph 53 and 54 note that the filter value are vertically and horizontally symmetric about the center pixels meaning that pixel the same distance from the center pixel [the output location] will have the same value see also paragraph 51 the first region could be for example all of the corner pixels with a value of one ).
Re claim 7 Tamura discloses wherein the first region is peripheral to a second region the at least a portion of pixel locations in the image frame, the second region containing the output pixel location. (see also paragraph 51 the first region could be for example all of the corner pixels with a value of 1, the second region could be center pixel which corresponds to the output pixel see paragraph 50)
Re claim 10 Tamura discloses wherein convolving image signal intensity values associated with pixel locations in the first region comprises: summing image signal intensity values associated with two or more pixel locations in the first region (see paragraph 53 -61 note that in the equation of paragraph 61 pixels with identical coefficients are summed then multiplied by the same value); multiplying the summed image signal intensity values by the same coefficient value to compute a product (see paragraph 53 -61 note that in the equation of paragraph 61 pixels with identical coefficients are summed then multiplied by the same value); and determining the output image signal intensity value based, at least in part, on the computed product. (see paragraph 53 -61 note that in the equation of paragraph 61 pixels with identical coefficients are summed then multiplied by the same value, this equation represents generating the output convolved value).
Re claim 11 Tamura discloses mapping image signal intensity values for at least some pixel locations in a second region of the image frame to a single image signal intensity value see paragraph 53 and equation 5 in particular in this case the pixel values of the 4 corners of the filter are all mapped to the sum of those values, then the sum of those values is multiplied by the filter coefficient which is the same for all the values); multiplying the single image signal intensity value by a coefficient value selected from the set of coefficient values to compute a product see paragraph 53 and equation 5 in particular in this case the pixel values of the 4 corners of the filter are all mapped to the sum of those values, then the sum of those values is multiplied by the filter coefficient which is the same for all the values) ; and determining the output image signal intensity value based, at least in part on the computed product (see paragraph 53 and 54 note that output of the convolution is based in part on the sum of values).
Re claim 12 Tamura discloses wherein mapping the image signal intensity values comprises averaging the image signal intensity values. (see paragraph 45 note that an average processing is performed on original pixels prior to the smoothing processing this will affect the summation i.e. single values calculated in paragraph 53)
Re claim 13 Tamura discloses selecting between and/or among multiple modes to convolve the image signal intensity values associated with the at least a portion of pixel locations in the image frame (see paragraph 72 73 note that multiple different levels of noise reduction may be selected corresponding to the multiple modes ), the multiple modes to convolve including at least a first mode comprising application of the same coefficient value to image signal intensity values of the multiple pixel locations in the first region (see paragraph 88 note that the same processing for reducing calculations as in the first embodiment may be applied see paragraph 53-61 note that certain location are mapped to the same pixel value).
Re claim 14 Tamura discloses wherein the same coefficient value is selected to be a reduced granularity coefficient value or a reduced precision value based, at least in part, on a location of the first region relative to the output pixel location (see paragraph 53 note that a chosen filter has symmetrical properties so filter elements in symmetrical locations have the same value)
Re claim 15 Tamura discloses
A method comprising: mapping original image signal intensity values of a plurality of pixel locations in a portion of an image frame to a single image signal intensity value to be representative of the pixel locations in an augmented portion of the image frame (see paragraph 53 and equation 5 in particular in this case the pixel values of the 4 corners of the filter are all mapped to the sum of those values, then the sum of those values is multiplied by the filter coefficient which is the same for all the values); and convolving image signal intensity values associated with the plurality of pixel locations in the augmented portion of the image frame by applying one or more kernel coefficients to the single image signal intensity value (see paragraph 53 and equation 5 in particular in this case the pixel values of the 4 corners of the filter are all mapped to the sum of those values, then the sum of those values is multiplied by the filter coefficient which is the same for all the values during the convolution operation)
the single image signal intensity value corresponding to original signal intensity values within a same region of the filter kernel (see paragraph 53 and equation 5 in particular in this case the pixel values of the 4 corners of the filter are all mapped to the sum of those values, then the sum of those values is multiplied by the filter coefficient which is the same for all the values, the region corresponds to the window of the filter). and having a same pixel color (see paragraph 40 “The processing explained here is performed independently for each of the three signals of RGB, but here, for simplification of explanation, a specific one color, for example, red is explained as an example.” Note that the filtering is performed independently for each color and therefore all the pixels will be of one color plane e.g. red).
Re claim 16 Tamura discloses determining the single image signal intensity value based, at least in part, on an average of the original image signal intensity values. (see paragraph 45 note that an average processing is performed on original pixels prior to the smoothing processing this will affect the summation i.e. single values calculated in paragraph 53)
Re claim 17 Tamura discloses determining the single image signal intensity value based, at least in part, on selection of a representative image signal intensity value from among the original image signal intensity values. (see paragraph 53 note that representative image values are selected and summed to generate single summed value)
Re claim 18 Tamura discloses kernel coefficients to be applied to image signal intensity values for pixels in the augmented portion of the image frame are selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the augmented portion of the image frame. (see paragraph 53 and equation 5 in particular in this case the pixel values of the 4 corners of the filter are all mapped to the sum of those values, then the sum of those values is multiplied by the filter coefficient which is the same for all the values during the convolution operation).
Re claim 20 Tamura discloses wherein the original image signal intensity values of the plurality of pixel locations are mapped to the single image intensity value and the one or more kernel coefficients are applied to the single image signal intensity value responsive to a mode configured at runtime (see paragraph 73 in the present embodiment, a configuration is explained in which it is made possible to switch the level of noise reduction by switching weight coefficients of a filter and correction values (that is, parameters) in accordance with a setting value set by a user. Explanation of the configuration of the image forming apparatus, the overview of the apparatus, and the duplicated processing flow, which are the same as those of the first embodiment, is omitted. The mode corresponds to the described setting.).
Re claim 21 Tamura discloses
An apparatus comprising: a memory storage device; one or more processors coupled to the memory storage device, the one or more processors to (see paragraph 92 note that the invention may be implemented by a computer and memory storing software)
convolving image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame, (see paragraph 50 note that an input pixel value is convolved with a filter to get and output pixel) wherein:
kernel coefficients comprising part of a filter kernel to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame are selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region (see paragraph 53 note some of the filter coefficients for the filter window are selected to have the same value those pixels are summed) having a same pixel color (see paragraph 40 “The processing explained here is performed independently for each of the three signals of RGB, but here, for simplification of explanation, a specific one color, for example, red is explained as an example.” Note that the filtering is performed independently for each color and therefore all the pixels will be of one color plane e.g. red) and within a same region of the filter kernel (see paragraph 53 note that the same filter coefficients belong to the filter window corresponding to the region).
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(s ) 1, 2, 3, 6, 10, 11, 13 ,14 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rhee US 2019/0149134 in view of Shmunk US 2013/0156345
.
Re claim 1 Rhee discloses A method comprising: convolving image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame, thereby providing a filtered output (see fort example paragraph 21 and 22 note that a convolution filter [kernel coefficients] may be applied to an image to generate a convolution output)
wherein: kernel coefficients comprising part of a filter kernel to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame are selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region. within a same region of the filter kernel (see paragraph 12 note that the convolution filter may be optimized so that that the set of filter coefficients have increased numbers of identical non-zero weights. i.e. the same filter weights are applied to multiple locations see paragraph 28 note that filtering is applied to region of the input image and shifted).
Rhee does not expressly disclose filter applied to image signal intensity values having a same pixel color. Shmunk discloses a filter applied to image signal intensity values having a same pixel color (see paragraph 61 note that a neural network as a part of a filter may be applied to each image channel independently). The motivation to combine is that Rhee discloses “The convolution logic 104 may be representative of any type of logic that performs convolution operations by applying a filter to input data, such as a machine learning algorithm, neural network (e.g., a convolutional neural network (CNN)), signal processing applications, and the like. The convolution logic 104 may implement any number and type of convolution operations, such as spatial dot products, fast Fourier transform (FFT), implementations of the Coppersmith-Winograd algorithm, and the like.” (see paragraph 20) One of ordinary skill in the art could have easily applied the principles of Rhee to enhance the neural network of Shumk. Therefore, it would have been obvious to one of ordinary skill in the art to combine Rhee and Shumk to reach the aforementioned advantage.
Re claim 2 Rhee discloses pixel locations in the first region are mapped to the same coefficient value of the set of coefficient values based, at least in part, on full-granularity coefficient values computed for the pixel locations in the first region (see paragraph 25 note that the spatial redundance of an the convolution filter 102 [i.e. the full granularity filter] [see also paragraph 21 and 22] may be reduced by lowering the variance to increase the likelihood of identical weight value i.e. multiple pixel values are mapped to the same weight).
Re claim 3 Rhee discloses wherein the same coefficient value is computed based, at least in part, on full-granularity coefficient values including at least some of the full-granularity coefficient values computed for the pixel locations. (see paragraph 25 note that the spatial redundance of the convolution filter 102 [i.e. the full granularity filter] [see also paragraph 21 and 22] may be reduced by lowering the variance to increase the likelihood of identical weight value i.e. multiple pixel values are mapped to the same weight).
Re claim 6 Rhee discloses the same coefficient value is selected to be applied to the image signal intensity values of the multiple pixel locations based, at least in part, a location of the first region relative to the output pixel location. (see paragraph 26 note that a filter optimizer may reduce the spatial granularity of the filter based on a shift operation (i.e. changing location of the first region relative to the output) to create more identical filter coefficients).
Re claim 10 Rhee discloses wherein convolving image signal intensity values associated with pixel locations in the first region comprises: summing image signal intensity values associated with two or more pixel locations in the first region; multiplying the summed image signal intensity values by the same coefficient value to compute a product; and determining the output image signal intensity value based, at least in part, on the computed product (see paragraph 25 “in such an example, if the optimized convolution filter 103 has weight values [w.sub.0, w.sub.1, . . . , w.sub.n] that are identical non-zero values, and [x.sub.0, x.sub.1, . . . , x.sub.n] are input values from the input 105, the convolution logic 104 may be configured to compute a product of sums ((x.sub.0+x.sub.1+ . . . +x.sub.n)*w.sub.0), which requires fewer addition and multiplication operations than computing the sum of products ((w.sub.0*x.sub.0)+(w.sub.1*x.sub.1)+ . . . +(w.sub.n*x.sub.n)). Doing so generates an instance of the convolution logic 104 that has a reduced number of instructions (and/or operations) relative to unoptimized instances of the convolution logic “note that input values with a same weight value are summed then multiplied by the identical weight to determine the output of the convolution).
Re claim 11 Rhee discloses mapping image signal intensity values for at least some pixel locations in a second region of the image frame to a single image signal intensity value; multiplying the single image signal intensity value by a coefficient value selected from the set of coefficient values to compute a product; and determining the output image signal intensity value based, at least in part on the computed product (see paragraph 25 “in such an example, if the optimized convolution filter 103 has weight values [w.sub.0, w.sub.1, . . . , w.sub.n] that are identical non-zero values, and [x.sub.0, x.sub.1, . . . , x.sub.n] are input values from the input 105, the convolution logic 104 may be configured to compute a product of sums ((x.sub.0+x.sub.1+ . . . +x.sub.n)*w.sub.0), which requires fewer addition and multiplication operations than computing the sum of products ((w.sub.0*x.sub.0)+(w.sub.1*x.sub.1)+ . . . +(w.sub.n*x.sub.n)). Doing so generates an instance of the convolution logic 104 that has a reduced number of instructions (and/or operations) relative to unoptimized instances of the convolution logic” note that input values with a same weight value are summed then multiplied by the identical weight to determine the output of the convolution the sum of pixel values could be considered the mapped value).
Re claim 13 Rhee discloses selecting between and/or among multiple modes to convolve the image signal intensity values associated with the at least a portion of pixel locations in the image frame, the multiple modes to convolve including at least a first mode comprising application of the same coefficient value to image signal intensity values of the multiple pixel locations in the first region. (see paragraph 25 note that mode where a product of sums is calculated to apply the identical filter coefficients is applied by summing the locations with the same value than multiplying by the identical coefficient, an additional mode may be ”suppress the most frequently occurring weight values to zero, resulting in more values for which no addition, multiplication, and/or MAC operations are required during convolution.” Therefore, the system selects between multiple modes, further note that non identical filter coefficients must be calculated by a sum of products, which may be a additional mode)
Re claim 14 Rhee discloses wherein the same coefficient value is selected to be a reduced granularity coefficient value or a reduced precision value based, at least in part, on a location of the first region relative to the output pixel location (see paragraph 26 note that a filter optimizer may reduce the spatial granularity of the filter based on a shift operation (i.e. changing location of the first region relative to the output) to create more identical filter coefficients,).
Re claim 21 Rhee discloses An apparatus comprising: a memory storage device; one or more processors coupled to the memory storage device, the one or more processors (see paragraph 19 note that elements may be implemented by software stored in memory and a processor)to: convolving image signal intensity values associated with at least a portion of pixel locations in an image frame with kernel coefficients to provide an output image signal intensity value mapped to an output pixel location in the image frame, (see fort example paragraph 21 and 22 note that a convolution filter [kernel coefficients] may be applied to an image to generate a convolution output )
wherein: kernel coefficients to be applied to image signal intensity values for pixels in a first region of the at least a portion of pixel locations in the image frame to be selected from a set of coefficient values such that a same coefficient value is to be applied to image signal intensity values of multiple pixel locations in the first region. (see paragraph 12 note that the convolution filter may be optimized so that that they have increased numbers of identical non-zero weights. i.e. the same filter weights are applied to multiple locations).
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rhee US 2019/0149134 and Shmunk US 2013/0156345 in view of Lee et al US 2020/0372340.
Re claim 4 Rhee and Shmunk disclose all the elements of claim 1 and increasing the number of identical coefficient values (see Rhee paragraph 12). Rhee and Shmunk does not expressly disclose wherein the same coefficient value is computed as an average of the full-granularity coefficient values. Lee discloses herein the same coefficient value is computed as an average of the full-granularity coefficient values (see paragraph 64 using an average of constituent weight parameter) The motivation to combine is “Convolution parameter optimization aims to achieve maximum accuracy with maximum optimization (reduction of computation)”. One or ordinary skill in the art could have easily increased the number of identical coefficients by averaging to reduce the computation. Therefore, it would have been obvious to one of ordinary skill in the art to combine Rhee Shmunk and Lee to reach the aforementioned advantage.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rhee US 2019/0149134 and Shmunk US 2013/0156345 in view of Edso US2024/0062063.
Re claim 5 Rhee and Shmunk discloses all the elements of claim 1 and increasing the number of identical coefficient values (see Rhee paragraph 12). Rhee and Shmunk does not expressly disclose, wherein the pixel locations in the first region are mapped to the same coefficient value based, at least in part, on an association of the full-granularity coefficient values with a range of values including the same coefficient value. Edso discloses wherein the pixel locations in the first region are mapped to the same coefficient value based, at least in part, on an association of the full-granularity coefficient values with a range of values including the same coefficient value (see paragraph 48 note that coefficients are given the same value by “binning” i.e all the elements in the bin [i.e. range] are given the same value.). The motivation to combine is to generate a reduced set of weight values (See paragraph 48). The examiner notes that one of ordinary skill in the art could have easily increased the number of identical coefficients as in Rhee using the method of Edso. Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Rhee Shmunk and Edso to reach the aforementioned advantage.
Claim(s ) 8 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tamura US 2019/0050967 in view of Schepelmann US 2012/0212638.
Re claim 8 Tamura discloses all of the features of claim 7. Tamura does not expressly disclose herein: the first region is at a vertical periphery to the second region; a single kernel coefficient is applied to image signal intensity values of multiple pixel locations in the first region extending in a vertical direction; and kernel coefficients are applied with full granularity in a horizontal dimension. Schepelmann discloses wherein: the first region is at a vertical periphery to the second region; a single kernel coefficient is applied to image signal intensity values of multiple pixel locations in the first region extending in a vertical direction; and kernel coefficients are applied with full granularity in a horizontal dimension (see paragraph 22 and 23 note that the vertical Prewitt convolution kernel has the same coefficient in vertical columns and different values in the horizontal direction ). The motivation to combine is the determine vertical edge strength (see Schepelmann paragraph 23) with reduced multiplications see Tamura paragraph 53). One of ordinary skill in the art could have easily applied the faster convolution principles of Tamura to additional types of filters such as the operator in Schepelmann to speed up the operation of Schepelmann. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Schepelmann and Tamura.
Re claim 9 Tamura discloses all of the features of claim 7. Tamura does not expressly disclose the first region is at a lateral periphery to the second region; a single kernel coefficient is applied to image signal intensity values of multiple pixel locations in the first region extending in a horizontal direction; and kernel coefficients are applied with full granularity in a vertical dimension. Schepelmann discloses the first region is at a lateral periphery to the second region; a single kernel coefficient is applied to image signal intensity values of multiple pixel locations in the first region extending in a horizontal direction; and kernel coefficients are applied with full granularity in a vertical dimension (see paragraph 22 and 23 note that the vertical Prewitt convolution kernel has the same coefficient in horizontal direction and different values in the vertical direction ). The motivation to combine is the determine horizontal edge strength edge strength (see paragraph 22) with reduced multiplications (see Tamura paragraph 53). One of ordinary skill in the art could have easily applied the faster convolution principles of Tamura to additional types of filters such as the operator in Schepelmann to speed up the operation of Schepelmann. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Schepelmann and Tamura.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Tamura US 2019/0050967 in view of Taguchi US 2014/0176760.
Re claim 19 Tamura discloses all of the element of claim 15 Tamura does not expressly disclose wherein: the image frame comprises a multi-color channel image frame; and the plurality of pixel locations in the augmented portion of the image frame are dis-contiguous and associated with a same color channel. Taguchi discloses wherein: the image frame comprises a multi-color channel image frame; and the plurality of pixel locations in the augmented portion of the image frame are dis-contiguous and associated with a same color channel (see paragraph 69 and 70 note that a single color channel is selected and only pixels of that color channel is used which are discontinuous see figures 8-10, and the same color value). The motivation to combine is to reduce the computation costs of the convolution unit (see paragraph 70). One of ordinary skill in the art could have easily applied the method of Tamura to one color channel of a dis-contiguous frame as disclosed in Taguchi to reduce the computational load. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Tamura and Taguchi to reach the aforementioned advantage.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN T MOTSINGER whose telephone number is (571)270-1237. The examiner can normally be reached 9AM-5PM.
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/SEAN T MOTSINGER/Primary Examiner, Art Unit 2673
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