DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Specification
The use of the terms “Apple Mac OS/X”, “iOS”, “Linux”, and “Wi-Fi”, which is a trade name or a mark used in commerce, has been noted in this application. The term should be accompanied by the generic terminology; furthermore the term should be capitalized wherever it appears or, where appropriate, include a proper symbol indicating use in commerce such as ™, SM , or ® following the term.
Although the use of trade names and marks used in commerce (i.e., trademarks, service marks, certification marks, and collective marks) are permissible in patent applications, the proprietary nature of the marks should be respected and every effort made to prevent their use in any manner which might adversely affect their validity as commercial marks.
The disclosure is objected to because of the following informalities: Paragraph 25, “statistic module” should be “statistics module”.
Appropriate correction is required.
Claim Objections
Claim 5 is objected to because of the following informalities: “compresse” should be “compress”. Appropriate correction is required.
Claim 7 is objected to because of the following informalities: “configured to performs” should be “configured to perform”. Appropriate correction is required.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 10-11, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ridge et al. (US 20160286226 A1).
Claims 1, 10-11, and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Ridge et al. (US 20160286226 A1), hereinafter referred to as Ridge.
In regards to claim 1, Ridge discloses a HDR (High Dynamic Range) tone mapping system comprising one or more processors configured to: receive an input image and extract semantic information from the input image (Paragraphs 8, 10, 28, and 96, Paragraph 96 deals with acquiring semantic information regarding the bitstream which would imply a device that acquires that information being included along with paragraphs 8 and 10 covering tone mapping and HDR respectively with paragraph 28 disclosing processors); decompose the input image to a high-bit base layer and a detail layer according to the semantic information (Paragraph 87 and 96, Paragraph 87 specifies two separate layers including a base layer and an enhancement layer which is analogous to the detail layer and 96 details that sematic information can be used in the specification of layers); generate statistics of pixels of the input image according to the semantic information (Paragraph 219, This paragraph describes that statistics may be acquired that can be used in the tone mapping with the local adaptation described including covering a variance in values would cover the variance in semantic labels); generate a tone curve according to the statistics of the pixels (Paragraphs 229 and 230, The curves described are analogous to the tone curves due to their relationship with the tone mapping operators and 230 describes that the curves are affected by the luminance which is a statistic of the pixels); compress the base layer having a first bit depth to a base layer having a second bit depth less than the first bit depth according to the tone curve, the statistics and the semantic information (Paragraphs 83, 98, 229, and 230, Paragraph 83 describes that compression can be done to the images which includes the base layer to make them more compact by making the original high bit rate into the low bit rate with the compression done by an encoder, the semantics are described to be used in paragraph 98 with 229 covering the curves being used in tone mapping and the luminance values affecting their use in the compression process); tune the detail layer according to the semantic information and the statistics to generate an adjusted detail layer (Paragraphs 199 and 200, This describes a color component adjustment process which would constitute changing the details of the image with the luma ranges acting as a statistic and 199 further specifies that label pictures can be used which would include semantic labels or semantic information); combine the adjusted detail layer and the low-bit base layer to generate an output image (Paragraph 89 and abstract, Describes a reconstructor that reconstructs the image and outputs a final reconstructed image the combination of the enhancement data which would be the detail layer and the LDR would constitute the generation of an output image).
In regards to claim 10, Ridge discloses wherein the input image has 18 bits to 24 bits per pixel, and the output image has 8 bits to 12 bits per pixel (Paragraphs 2 and 5, Paragraph 5 specifies that HDR, the input image, can be 12 bits and upward which would encompass 18-24 bits. LDR displays would be implied to be less than 12 bits which paragraph 2 uses 8 bits and 10 bits which would fall within the range of 8 bits to 12 bits.).
In regards to claim 11, it is similar to claim 1, and it is similarly rejected.
In regards to claim 20, it is similar to claim 10, and it is similarly rejected.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 2-6 and 12-16 are rejected under 35 U.S.C. 103 as being unpatentable over Ridge et al. (US 20160286226 A1), hereinafter referred to as Ridge, in view of Amthor et al. (US 20220076395 A1), hereinafter referred to as Amthor.
In regards to claim 2, Ridge does not explicitly disclose the limitations of this claim.
However, Amthor does disclose wherein the one or more processors are further configured to: assign a semantic label to each pixel of the input image to generate at least one semantic object in the input image (Paragraph 16, Describes the use of semantic labels on regions of pixels which means the label would implicitly correspond to all the pixels and describes the identification of semantic objects in the image); and the semantic information comprises the semantic label of each pixel of the input image and the semantic object in the input image (Paragraph 16, Describes the use of semantic labels on regions of pixels which means the label would implicitly correspond to all the pixels and describes the identification of semantic objects in the image).
Therefore, it would have been prima facie obvious to combine the disclosures of Amthor and Ridge as it would have led to a predictable increase in the identification of objects in the image. The identification of specific semantic objects would allow for easier identification of the various objects that would be within an image which would allow for easier improvements of an image. As such, it would have been prima facie obvious to combine these disclosures.
In regards to claim 3, Ridge discloses wherein the statistics of the pixels of the input image comprises a luminance distribution of pixels and color distribution of the pixels corresponding to the semantic object in the input image (Paragraphs 107 and 227, Describes the usage of luminance values and color distribution as relevant statistics).
In regards to claim 4, Ridge discloses wherein the one or more processors are further configured to generate the tone curve corresponding to the semantic object in the input image according to the luminance distribution of the pixels corresponding the semantic object (Paragraphs 229 and 230, The curves described are analogous to the tone curves due to their relationship with the tone mapping operators and 230 describes that the curves are affected by the luminance which is a statistic of the pixels).
In regards to claim 5, Ridge discloses wherein the one or more processors are further configured to compresse pixels belonging to the semantic object in the base layer having the first bit depth together according to the tone curve, the statistics and the semantic information corresponding to the semantic object (Paragraphs 83, 98, 229, and 230, Describes that compression can be done to the images to make them more compact with the compression done by an encoder, the semantics are described to be used in paragraph 98 with 229 covering the curves being used in tone mapping and the luminance values affecting their use in the compression process).
In regards to claim 6, Ridges discloses wherein the one or more processors are further configured to tune pixels belonging to the semantic object in the detail layer together according to the semantic information and the statistics (Paragraphs 199 and 200, This describes a color component adjustment process which would constitute changing the details of the image with the luma ranges acting as a statistic and 199 further specifies that label pictures can be used which would include semantic labels or semantic information).
In regards to claim 12, it is similar to claim 2, and it is similarly rejected.
In regards to claim 13, it is similar to claim 3, and it is similarly rejected.
In regards to claim 14, it is similar to claim 4, and it is similarly rejected.
In regards to claim 15, it is similar to claim 5, and it is similarly rejected.
In regards to claim 16, it is similar to claim 6, and it is similarly rejected.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Ridge et al. (US 20160286226 A1), hereinafter referred to as Ridge, in view of Amthor et al. (US 20220076395 A1), hereinafter referred to as Amthor, as applied to claims 2-6 and 12-16 above, and further in view of Yoshiharu et al. (JP 2015164512 A), hereinafter referred to as Yoshiharu.
In regards to claim 7, neither Ridge nor Amthor disclose wherein the one or more processors are configured to performs edge preserving filtering to preserve an edge of a semantic object of the plurality of semantic objects in the input image.
However, Yoshiharu does disclose wherein the one or more processors are further configured to performs edge preserving filtering to preserve an edge of a semantic object of the plurality of semantic objects in the input image (Paragraph 39, Discloses the use of edge preserving filters and how it preserves the various objects in the image by only allowing smaller amplitudes to be smoothed over).
It would have been prima facie obvious to combine these disclosures. As the usage of an edge preserving filter would have led to a predictable increase in accuracy as the preservation of the edges would allow for the shapes to be more accurate. As the edges are kept accurate over the various filters, this would allow for shapes to maintain their unique shapes more easily which would allow for easier semantic identification. As such, it would have been prima facie obvious to combine these disclosures.
In regards to claim 17, it is similar to claim 7, and it is similarly rejected.
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Ridge et al. (US 20160286226 A1), hereinafter referred to as Ridge, in view of Ha et al. (US 20230343025 A1), hereinafter referred to as Ha.
In regards to claim 8, Ridge does not explicitly disclose wherein the semantic information is extracted by a fully convolutional network (FCN), a U-Net, a SegNet, and/or a Deeplab.
However, Ha does disclose wherein the semantic information is extracted by a fully convolutional network (FCN), a U-Net, a SegNet, and/or a Deeplab (Paragraph 59, This discloses the use of a fully convolutional network which is a specific specialized network designed to derive semantic meaning so it is implied to work as a semantic segmentation model).
It would have been prima facie obvious to combine the teachings of Ha and Ridge as the usage of a fully convolutional network would allow for a predictable increase in accuracy. There are wide variety of machine learning models and neural networks which are made for a variety of tasks. However, fully convolutional networks are specifically designed for the process of semantic segmentation as such, this would be predictably better than other forms of neural networks or machine learning processes.
In regards to claim 18, it is similar to claim 8, and it is rejected similarly.
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ridge et al. (US 20160286226 A1), hereinafter referred to as Ridge, in view of Yoshiharu et al. (JP 2015164512 A), hereinafter referred to as Yoshiharu.
In regards to claim 9, Ridge does not disclose wherein the base layer having the first bit depth comprises spatially smooth components of the input image, and the detail layer comprises edge and texture components of the input image.
However, Yoshiharu does disclose wherein the base layer having the first bit depth comprises spatially smooth components of the input image, and the detail layer comprises edge and texture components of the input image (Paragraph 51, The paragraph describes dividing the layers with one layer representing mid and high frequency components, which according to the specification would map to edge and texture, with another representing the low frequency components which would map according to the specification to the spatially smooth components).
It would have been prima facie obvious to combine the disclosures of Ridge and Yoshiharu. As sorting the respective frequencies would lead to a predictable increase in the ability to modify the final image. As the splitting of the various frequencies into different levels in the layers would allow for the
In regards to claim 19, it is similar to claim 9, and it is similarly rejected.
Response to Amendment
The amendments entered 11/24/2025 have been considered in full. These amendments overcome the 112(f) interpretations and the various 112(b) rejections made for the claims. However, these amendments did not overcome objections to the specification, and they introduced some minor informalities to the claims. As such, those are reiterated here. Further, the amendments made do not overcome the 35 U.S.C. 102 rejections or the 35 U.S.C. 103 rejections.
Response to Arguments
Applicant's arguments filed 11/24/2025 have been fully considered but they are not persuasive.
In regards to Ridge not disclosing the extraction of semantic information from the input image, the cited section recites Ridge extracting semantic information from the bitstream that carries the image, as such, since the BRI of “extracting information from the input image” is very broad, Ridge would read upon the claim. If the semantic information is limited to the grounds of object identification as disclosed in the arguments, it should be recited within the claims to further narrow the BRI of semantic information into what is intended.
In regards to the “according to” limitations, Ridge does disclose in paragraph 96 that the semantic information is used in the encoding and decoding process, and paragraph 87 discloses the encoding and decoding process being used in decomposition which would be within a BRI.
Paragraph 219 does utilize semantics as it discloses that the tone mapping is locally adaptive where it changes the function based on the spatially varying characteristics of the video. This would be within the BRI of semantic regions as they are based on features from parts of the video.
The argument, then, just says that Ridge doesn’t disclose “using tone curves, statistics, and semantic information” to compress without anything more. However, the recited paragraphs of 83, 98, 229, and 230 all cover these aspects and go over how they impact the encoding and decoding process that is used for compression.
Then it states that the color adjustment is not a semantic-driven tuning based on identified objects, but the claim language only recites, “tuning… according to semantic information” which the recited paragraphs do tune the image according to semantic information. As such, the arguments made are not persuasive.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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CONOR AIDAN. O'MALLEY
Examiner
Art Unit 2675
/CONOR A O'MALLEY/ Examiner, Art Unit 2675
/ANDREW M MOYER/ Supervisory Patent Examiner, Art Unit 2675