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 .
Claim Objections
Claims 1 and 18 and 15 are objected to because of the following informalities:
Claims 1 and 18 and 15 recites the phrase “with which” in line 2, line 4 and line 6 respectively. The Examiner suggests replacing the phrase with the word ‘that’ to clarify the claim language.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation 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 broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function. Such claim limitation(s) is/are:
The phrase “computer device” in claim 1, line 1, have a structure associated with a processor.
The phrase “computer device” in claim 8, line 2, have a structure associated with a processor.
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 recites “subsequent to producing the modified gain map, and prior to modifying the digital image: generating a histogram for the modified gain map; modifying the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination thereof, based on the histogram, to produce modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof; adjusting the modified gain map based on the histogram, the modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof”., however, the claim is convoluted and therefore, unclear. The first portion of the claim states that “generating a histogram for the modified gain map”, then the headroom, midtone and so forth are modified based on the histogram and then, this adjusted gain is again modified by the histogram. From the above step, it would appear that adjustment of the gain by the histogram would cancel the effect of the modification done by the headroom, midtone and so forth. The Examiner is unable to ascertain the bounds of the claim and therefore renders the claim indefinite.
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.
Claims 1, 7-8 and 14-15 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Chan et al (Pub No.: US20240223910).
Regarding independent claim 1, Chan teaches a method for processing a digital image (method/system for gain generation based on a digital image – see [p][002]), the method comprising, by a computing device (computing device, 102 – see Fig 1 and [p][0032]):
receiving the digital image from an input source (input devices such as camera – see [p][0117]) with which the computing device is communicatively coupled ([a]ccordingly, in an interconnected device embodiment, implementation of functionality described herein is distributable throughout the system 1200. For example, the functionality is implementable in part on the computing device 1202 as well as via the platform 1216 that abstracts the functionality of the cloud 1214 - see [p][0117][0126]), wherein the digital image includes:
(i) pixel information (for e.g. the bit depth – see [p][0024]), and
(ii) metadata that defines a plurality of properties of the digital image ([t]he metadata 134 is also configurable to store per-channel minimum and maximum gain map 132 values, e.g., as log2 values – see [p][0055]);
determining headroom metrics, midtone metrics, highlight metrics, shadow metrics, diffuse white metrics, or some combination thereof (a minimum, average (arithmetic mean), maximum pixel luminance of the HDR digital image 204 and HDR capabilities available (e.g., enough highlight headroom) to display a full HDR digital image without clipping – see [p][0055][0076]), based on the digital image (see [p][0055]);
adjusting a gain map for the digital image based on the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination thereof, to produce a modified gain map ([t]he minimum and maximum HDR capacity values are specified, in one example, in a log.sub.2 space and are set (e.g., by an author or authoring application) to control how the gain map 132 is scaled – see [p][0055]);
producing a supplemental digital image (digital image file 226 – see [p][0059] and Fig 2) based on the digital image (base digital image – see [p][0020] ) and the modified gain map ([t]he normalized gain map is then scaled to a range of “0” to “2N−1” (e.g., 255 for eight bits), is quantized, and clipped created from initial gain map – see Fig 4); and
causing the supplemental digital image to be output on a display device (a system 800 in an example implementation showing operation of the HDR display system 124 of FIG. 1 in greater detail as applying a gain map and displaying a digital image – see [p][0060] and Fig 8).
Regarding claim 7, Chan teaches the method of claim 1, wherein the plurality of properties define characteristics of the digital image, characteristics of a scene that corresponds to the digital image, circumstances under which the scene was captured, or some combination thereof (for e.g. hdrgm:BaseRendition=“SDR” and hddrgm:AveragePixelLuminanceSDR=“0.053161 – see [p][0106]”).
Regarding independent claim 8, Chan teaches a non-transitory computer readable storage medium (memory/storage, 1212 – see [p][0116] and Fig 12) configured to store instructions (memory/storage 1212 that stores instructions – see [p][0116]) that, when executed by at least one processor (see [p][0115]) included in a computing device (computing device, 102 – see Fig 1 and [p][0032]), cause the computing device to process a digital image, by carrying out steps (method/system for gain generation based on a digital image – see [p][002]) that include:
receiving the digital image from an input source (input devices such as camera – see [p][0117]) with which the computing device is communicatively coupled ([a]ccordingly, in an interconnected device embodiment, implementation of functionality described herein is distributable throughout the system 1200. For example, the functionality is implementable in part on the computing device 1202 as well as via the platform 1216 that abstracts the functionality of the cloud 1214 - see [p][0117][0126]), wherein the digital image includes:
(i) pixel information (for e.g. the bit depth – see [p][0024]), and
(ii) metadata that defines a plurality of properties of the digital image ([t]he metadata 134 is also configurable to store per-channel minimum and maximum gain map 132 values, e.g., as log2 values – see [p][0055]);
determining headroom metrics, midtone metrics, highlight metrics, shadow metrics, diffuse white metrics, or some combination thereof (a minimum, average (arithmetic mean), maximum pixel luminance of the HDR digital image 204 and HDR capabilities available (e.g., enough highlight headroom) to display a full HDR digital image without clipping – see [p][0055][0076]), based on the digital image (see [p][0055]);
adjusting a gain map for the digital image based on the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination thereof, to produce a modified gain map ([t]he minimum and maximum HDR capacity values are specified, in one example, in a log.sub.2 space and are set (e.g., by an author or authoring application) to control how the gain map 132 is scaled – see [p][0055]);
producing a supplemental digital image (digital image file 226 – see [p][0059] and Fig 2) based on the digital image (base digital image – see [p][0020]) and the modified gain map ([t]he normalized gain map is then scaled to a range of “0” to “2N−1” (e.g., 255 for eight bits), is quantized, and clipped created from initial gain map – see Fig 4); and
causing the supplemental digital image to be output on a display device (a system 800 in an example implementation showing operation of the HDR display system 124 of FIG. 1 in greater detail as applying a gain map and displaying a digital image – see [p][0060] and Fig 8).
Regarding claim 14, which corresponds to claim 7 except for reciting a different statutory category of non-transitory computer readable storage medium. Therefore, the rejection analysis of claim 7 is fully applicable to claim 14.
Regarding independent claim 15, Chan teaches a computing device (1200 – see Fig 12) configured to process a digital image (system for gain generation based on a digital image – see [p][0002), the computing device comprising: at least one processor (see [p][0115]); and at least one memory storing instructions that (memory/storage 1212 that stores instructions – see [p][0116]), when executed by the at least one processor, cause the computing device to carry out steps that include:
receiving the digital image from an input source (input devices such as camera – see [p][0117]) with which the computing device is communicatively coupled ([a]ccordingly, in an interconnected device embodiment, implementation of functionality described herein is distributable throughout the system 1200. For example, the functionality is implementable in part on the computing device 1202 as well as via the platform 1216 that abstracts the functionality of the cloud 1214 - see [p][0117][0126]), wherein the digital image includes:
(i) pixel information (for e.g. the bit depth – see [p][0024]), and
(ii) metadata that defines a plurality of properties of the digital image ([t]he metadata 134 is also configurable to store per-channel minimum and maximum gain map 132 values, e.g., as log2 values – see [p][0055]);
determining headroom metrics, midtone metrics, highlight metrics, shadow metrics, diffuse white metrics, or some combination thereof (a minimum, average (arithmetic mean), maximum pixel luminance of the HDR digital image 204 and HDR capabilities available (e.g., enough highlight headroom) to display a full HDR digital image without clipping – see [p][0055][0076]), based on the digital image (see [p][0055]);
adjusting a gain map for the digital image based on the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination thereof, to produce a modified gain map ([t]he minimum and maximum HDR capacity values are specified, in one example, in a log.sub.2 space and are set (e.g., by an author or authoring application) to control how the gain map 132 is scaled – see [p][0055]);
producing a supplemental digital image (digital image file 226 – see [p][0059] and Fig 2) based on the digital image (base digital image – see [p][0020]) and the modified gain map ([t]he normalized gain map is then scaled to a range of “0” to “2N−1” (e.g., 255 for eight bits), is quantized, and clipped created from initial gain map – see Fig 4); and
causing the supplemental digital image to be output on a display device (a system 800 in an example implementation showing operation of the HDR display system 124 of FIG. 1 in greater detail as applying a gain map and displaying a digital image – see [p][0060] and Fig 8).
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 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 of this title, 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 2, 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al (Pub No.: US20240223910) in view of Duan et al (NPL titled: Tone-mapping high dynamic range images by novel histogram adjustment) in view of Nakajima et al (Pub No.: 20040228522).
(As best understood) Regarding claim 2, Chan does not explicitly teach the method of claim 1, further comprising, subsequent to producing the modified gain map, and prior to modifying the digital image: generating a histogram for the modified gain map; modifying the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination thereof, based on the histogram, to produce modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof.
However, Duan explicitly teaches subsequent to producing the modified gain map, and prior to modifying the digital image: generating a histogram for the modified gain map (see [p][003]); modifying the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination (see [p][003]) thereof, based on the histogram, to produce modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof; adjusting the modified gain map based on the histogram, the modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination (see [p][003]) thereof
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Chan of a method for processing a digital image, the method comprising, by a computing device with the teachings of Duan further comprising, subsequent to producing the modified gain map, and prior to modifying the digital image: generating a histogram for the modified gain map; modifying the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination thereof, based on the histogram, to produce modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof.
Wherein having Chan further comprising, subsequent to producing the modified gain map, and prior to modifying the digital image: generating a histogram for the modified gain map; modifying the headroom, midtone, highlight, shadow, diffuse white metrics, or some combination thereof, based on the histogram, to produce modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof.
The motivation behind the modification would have been for performing global histogram adjustment based tone mapping operator, which well reproduces global contrast for high dynamic range images and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic since both Chan and Duan relates to image enhancement, wherein Chan promotes consistency and predictability as to how digital images implement HDR functionality across applications, devices, and platforms and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic while Duan performs global histogram adjustment based tone mapping operator, which well reproduces global contrast for high dynamic range images (Please see Chan et al (Pub No.: US20240223910), [p][0019] and Duan et al (NPL titled: Tone-mapping high dynamic range images by novel histogram adjustment), see Abstract).
Note the discussion above, Yang in view of Duan does not explicitly teach adjusting the modified gain map based on the histogram, the modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof.
Nakajima explicitly teaches adjusting the modified gain map based on the histogram (FIG. 10(c), curve A.sub.1 is a cumulative histogram generated from the density histogram before the clipping, and curve A.sub.2 is a cumulative histogram generated from the density histogram after the clipping – see [p][0098]), the modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination (a primary color image, an intensity image in a hue/saturation/intensity space normalized in a cylindrical coordinate system; a means for analyzing the texture of the intensity image and dividing the intensity image into a plurality of regions on the basis of the result of the analysis; a means for executing density conversion of the intensity image by smoothing a histogram of each region; and a means for generating a primary color image by using the density-converted intensity image – see [p][0015]) thereof.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Chan as modified by Duan of a method for processing a digital image, the method comprising, by a computing device with the teachings of Nakajima adjusting the modified gain map based on the histogram, the modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof.
Wherein having Chan adjusting the modified gain map based on the histogram, the modified headroom, modified midtone, modified highlight, modified shadow, modified diffuse white metrics, or some combination thereof.
The motivation behind the modification would have been to create cumulative histogram generated from the density histogram after the clipping thus prevent excessive contrast emphasis and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic since both Chan and Nakajima relates to image enhancement, wherein Chan promotes consistency and predictability as to how digital images implement HDR functionality across applications, devices, and platforms and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic while Nakajima create cumulative histogram generated from the density histogram after the clipping thus prevent excessive contrast emphasis (Please see Chan et al (Pub No.: US20240223910), [p][0019] and Nakajima et al (Pub No.: 20040228522), see [p][0098]).
.
Regarding claim 9, which corresponds to claim 2 except for reciting a different statutory category of non-transitory computer readable storage medium. Therefore, the rejection analysis of claim 2 is fully applicable to claim 9.
Regarding claim 16, which corresponds to claim 2 except for reciting a different statutory category of a computing device. Therefore, the rejection analysis of claim 2 is fully applicable to claim 16.
Claims 3, 10 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al (Pub No.: US20240223910) in view of Muammar et al (Pub No.: 20030222991).
Regarding claim 3, Chan does not explicitly teach method of claim 1, wherein the shadow metrics are determined based on at least one image capture type that is associated with the digital image and stored within the metadata.
However, Yang explicitly teaches wherein the shadow metrics are determined based on at least one image capture type that is associated with the digital image and stored within the metadata ([t]he difference between the estimated pixel data (that exceeds 1.0 in the case of highlight clipping and in the case of shadow clipping that is less than 0) and the original pixel data can be saved as Metadata with the image for use by other image processing algorithms – see [p][0275])
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Chan of a method for processing a digital image, the method comprising, by a computing device with the teachings of Muammar wherein the shadow metrics are determined based on at least one image capture type that is associated with the digital image and stored within the metadata.
Wherein having Chan wherein the shadow metrics are determined based on at least one image capture type that is associated with the digital image and stored within the metadata.
The motivation behind the modification would have been for storing shadow values in a metadata to make intelligent use of this Metadata to improve the overall quality of images they generate and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic since both Chan and Yang relates to image enhancement, wherein Chan promotes consistency and predictability as to how digital images implement HDR functionality across applications, devices, and platforms and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic while Muammar stores shadow values in a metadata to make intelligent use of this metadata to improve the overall quality of images they generate (Please see Chan et al (Pub No.: US20240223910), [p][0019] and Muammar et al (Pub No.: 20030222991), [p][0275]).
Regarding claim 10, which corresponds to claim 3 except for reciting a different statutory category of non-transitory computer readable storage medium. Therefore, the rejection analysis of claim 3 is fully applicable to claim 10.
Regarding claim 17, which corresponds to claim 3 except for reciting a different statutory category of a computing device. Therefore, the rejection analysis of claim 3 is fully applicable to claim 17.
Claims 4-5, 11-12 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al (Pub No.: US20240223910) in view of GIUSEPPE et al (Pub No.: 20200159963).
Regarding claim 4, Chan does not explicitly teach the method of claim 1, wherein the diffuse white metrics are determined based on at least one material property classifier associated with the digital image, and/or at least one semantic mask associated with the digital image, that are stored within the metadata.
However, GIUSEPPE explicitly teaches wherein the diffuse white metrics are determined based on at least one material property classifier associated with the digital image, and/or at least one semantic mask associated with the digital image (the photograph may be transformed into a transformed photograph upon masking the set of human faces present in the photograph – see [p][0053]), that are stored within the metadata (metadata associated to the transformed photograph may be stored in the transformed image. In one aspect, the metadata facilitates to re-transform the transformed photograph to the photograph – see [p][0054]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Chan of a method for processing a digital image, the method comprising, by a computing device with the teachings of GIUSEPPE wherein the diffuse white metrics are determined based on at least one material property classifier associated with the digital image, and/or at least one semantic mask associated with the digital image.
Wherein having Chan wherein the diffuse white metrics are determined based on at least one material property classifier associated with the digital image, and/or at least one semantic mask associated with the digital image.
The motivation behind the modification would have been for facilitating a secure access to a photograph over a social networking platform by applying a masked to a set of human faces by one algorithm and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic since both Chan and Yang relates to image enhancement, wherein Chan promotes consistency and predictability as to how digital images implement HDR functionality across applications, devices, and platforms and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic while GIUSEPPE facilitates a secure access to a photograph over a social networking platform by applying a masked to a set of human faces by one algorithm (Please see Chan et al (Pub No.: US20240223910), [p][0019] and GIUSEPPE et al (Pub No.: 20200159963 ), see Abstract).
Regarding claim 5, Chan does not explicitly teach the method of claim 4, wherein the at least one semantic mask comprises a people mask, an animal mask, an eye mask, or some combination thereof.
However, GIUSEPPE explicitly teaches wherein the at least one semantic mask comprises a people mask (masking the set of human faces – see [p][0053]), an animal mask, an eye mask, or some combination thereof
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Chan of a method for processing a digital image, the method comprising, by a computing device with the teachings of GIUSEPPE wherein the at least one semantic mask comprises a people mask, an animal mask, an eye mask, or some combination thereof.
Wherein having Chan wherein the diffuse white metrics are determined based on at least one material property classifier associated with the digital image, and/or at least one semantic mask associated with the digital image.
The motivation behind the modification would have been for facilitating a secure access to a photograph over a social networking platform by applying a masked to a set of human faces by one algorithm and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic since both Chan and Yang relates to image enhancement, wherein Chan promotes consistency and predictability as to how digital images implement HDR functionality across applications, devices, and platforms and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic while GIUSEPPE facilitates a secure access to a photograph over a social networking platform by applying a masked to a set of human faces by one algorithm (Please see Chan et al (Pub No.: US20240223910), [p][0019] and GIUSEPPE et al (Pub No.: 20200159963 ), see Abstract).
Regarding claim 11, which corresponds to claim 4 except for reciting a different statutory category of non-transitory computer readable storage medium. Therefore, the rejection analysis of claim 4 is fully applicable to claim 11.
Regarding claim 12, which corresponds to claim 5 except for reciting a different statutory category of non-transitory computer readable storage medium. Therefore, the rejection analysis of claim 5 is fully applicable to claim 12.
Regarding claim 18, which corresponds to claim 4 except for reciting a different statutory category of a computing device. Therefore, the rejection analysis of claim 4 is fully applicable to claim 18.
Regarding claim 19, which corresponds to claim 5 except for reciting a different statutory category of a computing device. Therefore, the rejection analysis of claim 5 is fully applicable to claim 19.
Claims 6, 13 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Chan et al (Pub No.: US20240223910) in view of Yang et al (NPL titled: Detail-enhanced and brightness-adjusted exposure image fusion).
Regarding claim 6, Chan does not explicitly teach the method of claim 1, wherein the gain map is generated based on two or more exposure versions of the digital image that are associated with captures of a same scene.
However, Yang explicitly teaches wherein the gain map is generated based on two or more exposure versions (A(x,y) and B(x,y) – see Fig 2)) of the digital image that are associated with captures of a same scene (A(x,y) and B(x,y) – see Fig 2).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Chan of a method for processing a digital image, the method comprising, by a computing device with the teachings of Yang wherein the gain map is generated based on two or more exposure versions of the digital image that are associated with captures of a same scene.
Wherein having Chan wherein the gain map is generated based on two or more exposure versions of the digital image that are associated with captures of a same scene.
The motivation behind the modification would have been for implements a multiexposure image fusion which can enhance details, yet effectively improve brightness in the final result since and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic since both Chan and Yang relates to image enhancement, wherein Chan promotes consistency and predictability as to how digital images implement HDR functionality across applications, devices, and platforms and support backward compatibility while minimizing storage overhead and complexity of additional runtime display logic while Yang implemnts a multiexposure image fusion method which can enhance details, yet effectively improve brightness in the final result. (Please see Chan et al (Pub No.: US20240223910), [p][0019] and Yang et al (NPL titled: Detail-enhanced and brightness-adjusted exposure image fusion)).
Regarding claim 13, which corresponds to claim 6 except for reciting a different statutory category of non-transitory computer readable storage medium. Therefore, the rejection analysis of claim 6 is fully applicable to claim 13.
Regarding claim 20, which corresponds to claim 6 except for reciting a different statutory category of a computing device. Therefore, the rejection analysis of claim 6 is fully applicable to claim 20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Elwell et al (Pub No.: 20260112010) discloses a system (100) has a processing circuitry (102) for receiving a high dynamic resolution (HDR) image (110) comprising pixels, where each pixel comprises brightness values for each of color components. The processing circuitry applies a tone mapping algorithm to each pixel in the HDR image for generating a standard dynamic range (SDR) image with transformed brightness values of each of the color components. The gain map is generated using the HDR and SDR images (120). The gain map-based enhanced HDR image (130) is generated based on the SDR image and the gain map. An output is generated based on gain map based enhanced HDR.
BONNIER et al (Pub No.: 20240153054) discloses various techniques for utilizing gain maps. According to some embodiments, one technique for utilizing a gain map comprises (1) accessing an enhanced image that includes a high dynamic range (HDR) image and the gain map, (2) extracting the HDR image and the gain map from the enhanced image, (3) generating a standard dynamic range (SDR) image using the HDR image and the gain map, (4) receiving and applying first modification instructions against the HDR image, (5) generating second modification instructions based on at least the first modification instructions, (6) applying the second modification instructions to the SDR image, (7) generating a second gain map by comparing the HDR image against the SDR image or vice-versa, and (8) embedding the second gain map into the HDR image or the SDR image.
Jia et al (Pub No.: 20130294689) discloses techniques are provided to encode and decode image data comprising a tone mapped (TM) image with HDR reconstruction data in the form of luminance ratios and color residual values. In an example embodiment, luminance ratio values and residual values in color channels of a color space are generated on an individual pixel basis based on a high dynamic range (HDR) image and a derivative tone-mapped (TM) image that comprises one or more color alterations that would not be recoverable from the TM image with a luminance ratio image. The TM image with HDR reconstruction data derived from the luminance ratio values and the color-channel residual values may be outputted in an image file to a downstream device, for example, for decoding, rendering, and/or storing. The image file may be decoded to generate a restored HDR image free of the color alterations.
Johnson et al, (US Patent No.: 11715184) discloses devices, methods, and program storage devices for creating and/or displaying backwards-compatible High Dynamic Range (HDR) images are disclosed, comprising: obtaining two or more exposures of a scene; creating a gain map based on at least one of the two or more exposures, wherein the gain map comprises a plurality of pixels each corresponding to a portion of the scene, and wherein values of the pixels in the gain map comprise indications of a brightness level of the corresponding portions of the scene; combining the two or more exposures to form a first image; tone mapping the first image based on a Standard Dynamic Range (SDR) format to generate a first SDR image of the scene; and storing the first SDR image and created gain map in a first enhanced image file. The first enhanced image file may be, e.g., a HEIF, HEIC, PNG, GIF, JPEG, or other suitable file format.
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/ANDRAE S ALLISON/Primary Examiner, Art Unit 2673
June 18, 2026
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