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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on November 7, 2025 has been considered in part. However, no English-language translations for two of the cited foreign patent documents were submitted with the IDS, and therefore these two references have not been considered, as indicated by the lines drawn through those citations in the attached IDS. 37 CFR 1.98(3)(i) requires that a concise explanation of the relevance of each cited foreign patent document that is not in the English language.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation (BRI) using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The BRIs are used for purposes of searching for prior art, but cannot be incorporated into the claims. Claim limitations must be given their plain meaning unless such meaning is inconsistent with the specification. MPEP 2111.01.
BRIs for some of the claim limitations are provided below. Should Applicant believe that other interpretations are warranted, Applicant should point to the portions of the present disclosure that clearly show that a different interpretation is appropriate.
Claim Objections
Claim 1 is objected to because of the following informalities.
Claim 1 recites “a raw high-frequency image” generated from the raw image and “a high-frequency image” yielded by filtering the rendered image. Because of this dual usage of the phrase “high-frequency image”, the use of the phrase “the high-frequency image” in the last line of claim 1 is somewhat confusing. For improved clarity, the examiner suggests changing the phrase “the high-frequency image” recited in the last line of claim 1 to --the high-frequency image yielded by filtering the rendered image--.
Appropriate correction is required.
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.
Claims 1-4 and 8 are rejected under 35 U.S.C. §101 because the claimed invention is directed to an abstract idea without significantly more. Claims 1-4 fall into the statutory class of process. Claim 8 falls into the statutory class of machine. Notwithstanding that these claims fall into statutory classes, they are directed to ineligible subject matter, namely, an abstract idea.
The USPTO has enumerated groupings of abstract ideas that are firmly rooted in Supreme Court precedent as well as Federal Circuit decisions interpreting that precedent (See MPEP §2106.04(a)). The enumerated groupings of abstract ideas are defined as:
1) Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
2) Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
3) Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
Under Step 2A, Prong One of the Alice/Mayo test, a determination is made as to whether the claim recites one of the judicial exceptions, i.e., an abstract idea, a law of nature or a natural phenomenon. The operations recited in claim 1 are mathematical operations that fall under above enumerated grouping 1). All of the operations recited in independent claim 1 are mathematical manipulations of image data that produce a mathematical result.
Once it has been determined that the claim under examination recites an abstract idea, then Step 2A, Prong Two of the Alice/Mayo test must be performed to determine whether any additional elements are recited in the claim that integrate the abstract idea into a practical application (See MPEP §§2106.04(d), 2106.05(a)-(c) and (e)-(h)). The U.S. Supreme Court has distinguished between principles themselves, which are not patent eligible, and the integration of those principles into practical applications, which are patent eligible. See, e.g., Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 80, 84, 101 USPQ2d 1961, 1968-69, 1970 (2012).
To determine whether the claim as a whole integrates the abstract idea into a practical application, any additional elements that are recited in the claim (i.e., claim elements other than those that constitute the abstract idea) must be evaluated to determine whether they amount to significantly more than the judicial exception itself.
In claim 1, there are no additional elements other that the mathematical operations. Claims 2-4 recite additional mathematical operations, or further define mathematical operations recited in claim 1, but do not recite additional elements over and above the abstract idea. Since claims 1-4 do not recite any additional elements, the analysis ends, in which case Step 2B of the Alice/Mayo test, which is shown in the flowchart in MPEP
§
2106.04(II)(A) and discussed further in MPEP §§2106.05(a)-(c) and (e)-(h), is not performed Therefore, claims 1-4 are directed to ineligible subject matter and are therefore rejected under 35 U.S.C. §101.
Regarding claim 8, the only additional elements that are recited in the claim are a processor and memory for storing instructions for execution by the processor. Under Step 2A, Prong Two, a determination must be made as to whether the additional elements are indicative of integration into a practical application. Mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, are not an indicative of integration into a practical application. MPEP §2106.05(f). Therefore, the recitation of the processor and memory in claim 8 are not indicative of integration of the abstract idea into a practical application.
Even if the claim fails Step 2A, Prong Two of the Alice/Mayo test, the process then moves to Step 2B of the Alice/Mayo test. Under Step 2B, a determination must be made as to whether the additional limitations are indicative of an inventive concept. The considerations of Step 2A, Prong Two overlap the considerations of Step 2B. Under Step 2B, mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, are not an indicative of an inventive concept. MPEP §2106.05(f). Therefore, the recitation of the processor and memory in claim 8 are not indicative of an inventive concept. Therefore, claim 8 is directed to ineligible subject matter and is therefore rejected under 35 U.S.C. §101.
Regarding claim 5, this claim is directed to steps performed to generate a reconstructed raw image. While the steps include mathematical operations, the claim as a whole recites limitations that are indicative of integration into a practical application under Step 2A, Prong Two of the Alice/Mayo test. Under Step 2A, Prong Two, one of the considerations that is indicative of integration into a practical application is whether the claim recites limitations that purportedly achieve a technical improvement in a technical field, and whether the present disclosure provides a technical explanation of the solution for achieving the purported improvement. The present disclosure provides a detailed discussion of the manner in which the operations recited in claim 8 lead to a purported improvement in the accuracy with which the raw image is reconstructed. Therefore, this claim recites limitations that integrate the abstract idea into a practical application.
Allowable Subject Matter
Claims 5-7 are allowed.
Claim 1 would be allowable if rewritten to overcome the objection and the rejection under 35 U.S.C. §101.
Claims 2-4 and 8 would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and to overcome the rejections under 35 U.S.C. §101.
The following is an examiner’s statement of reasons for allowance:
Regarding claim 1, none of the art, taken alone or in combination, teaches or suggests the particular combination of steps recited in claim 1. Prior art exists that teaches some of the concepts recited in claim 1, such as generating and storing metadata that can later be used to reconstruct the raw image from a rendered image, such as a JPEG or sRGB image. For example, it is known in the art that generating and storing metadata based on the raw image and subsequently using the metadata for raw image reconstruction obviates the need to store the entire raw image in order to later accurately reconstruct the raw image. For example, an article entitled “Spatially Aware Metadata for Raw Reconstruction”, by Punnappurath et al., published January 1, 2021 in 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) (2021, Page(s): 218-226) (hereinafter referred to as “Punnappurath”) discloses generating and storing metadata that will later be used to reconstruct the raw image. The method involves sparsely sampling a demosaiced raw image and storing the samples as metadata along with the rendered sRGB image. The samples are used to estimate a de-rendering function that is later applied to the rendered sRGB image to recover the raw image. However, neither Punnappurath nor any of the other prior art, taken alone or in combination, teach or suggest the combination of steps recited in claim 1 of:
generating a raw low-frequency image and a raw high-frequency image from the raw image or the image derived therefrom using decomposition parameters;
subsampling the raw low-frequency image to generate sub-sampled data;
filtering the rendered image using the decomposition parameters to yield a high- frequency image; and
determining a reconstruction matrix, wherein a product of the reconstruction matrix and the high-frequency image equals the raw high-frequency image.
While Punnappurath does disclose subsampling the raw image, it does not disclose the combination of steps of generating a raw low-frequency image and a raw high-frequency image, sub-sampling the raw low-frequency image, filtering the rendered image to yield a high-frequency image, or determining a reconstruction matrix, wherein a product of the reconstruction matrix and the high-frequency image equals the raw high-frequency image. Even if the de-rendering function of Punnappurath can be interpreted as comprising a reconstruction matrix, Punnappurath does not teach or suggest that multiplying that matrix by a high-frequency image obtained by filtering the rendered sRGB image equals the raw high-frequency image. Punnappurath is silent regarding the frequency as it relates to the raw or rendered image data.
An article entitled “RAW Image Reconstruction using a Self-Contained sRGB-JPEG Image with only 64 KB Overhead”, by Nguyen et al., published June 1, 2016 in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016, Page(s): 1655-1663) (hereinafter referred to as “Nguyen”) also discloses generating and storing metadata from a raw image that will later be used to reconstruct the raw image. In Nguyem, in-camera model estimation is performed, which involves tone mapping, white-balance and color space matrix generation and gamut mapping. The corresponding parameters are embedded as metadata into the rendered JPEG file. During reconstruction of the raw image file, the metadata is extracted from the rendered JPEG file and used to reconstruct the raw image. However, Nguyen, taken alone or in combination with other prior art, does not teach or suggest the particular combination of steps recited in claim 1 and discussed above.
Regarding claims 2-4 and 8, these claims recite allowable subject matter due to their dependence from independent claim 1.
Regarding claim 5, this claim recites many of the same limitations that are recited claim 1, including those discussed above, but in the context of reconstructing the raw image. For the same reasons discussed above, the prior art does not teach or suggest the combination of limitations.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Publ. Appl. No. 2021/0160470 A1 discloses systems and methods for, given an input sRGB image that is rendered through an unknown camera ISP with an arbitrary white-balance setting, editing colors of the input sRGB image to make it appear as if it is re-rendered with a target WB setting.
U.S. Publ. Appl. No. 2019/0122340 A1 discloses an image processing apparatus, an image processing system, and recording medium capable of achieving both reduction of the amount of data and securement of reproducibility. An image processing apparatus generates compressed image data by compressing raw image data acquired by imaging an object into a JPEG format, restores the compressed image data to restored image data of a bmp format, and then acquires a first result by executing an image measurement processing on the restored image data. The image processing apparatus stores the compressed image data and the first result in association with each other.
U.S. Publ. Appl. No. 2010/0046849 A1 discloses restoration of images by vector quantization utilizing visual patterns is disclosed. One disclosed embodiment comprises restoring detail in a transition region of an unrestored image, by first identifying the transition region and forming blurred visual pattern blocks. These blurred visual pattern blocks are compared to a pre-trained codebook, and a corresponding high-quality visual pattern blocks is obtained. The high-quality visual pattern block is then blended with the unrestored image to form a restored image. The method may be performed on any unrestored image that has been lossily compressed or downsampled. The method first comprises extracting locations of the edge pixels in the image. This may be done in any suitable manner, including but not limited to applying directional filters to detect edge pixels and/or applying a high-pass filter to filter out low frequency components of the unrestored image.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL J SANTOS whose telephone number is (571)272-2867. The examiner can normally be reached M-F 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matt Bella can be reached at (571)272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANIEL J. SANTOS/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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