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 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 do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: Each “unit” claims 19, 21.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend 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 avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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(s) 18 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because claim(s) 18 is /are directed to a “storage medium". However, according to paragraph [0102] of the specification (e.g., “a storage medium (which may also be referred to more fully as a 'non-transitory computer-readable storage medium')” and the “storage medium may include, for example, one or more of a hard disk, a random-access memory (RAM), a read only memory (ROM), a storage of distributed computing systems, an optical disk (such as a compact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, a memory card, and the like”), the broadest reasonable interpretation of the "computer readable storage medium" covers a transitory propagating signal which is non-statutory subject matter. See In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007).
The examiner suggests amending the claim(s) to recite a “non-transitory computer-readable medium” storing a computer program or equivalent. Any amendment to the claims should be commensurate with its corresponding disclosure.
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.
Claim(s) 1-3, 10, 14-16, 18-22 is/are rejected under 35 U.S.C. 102(a)(1) or 102(a)(2) as being anticipated by Kokura (US 2020/0396415).
As to claim 1, Kokura discloses an image processing method comprising:
obtaining a captured image by image capturing using an optical apparatus (para. 0025, e.g., an image 108 obtained by capturing an athlete (object 104) is obtained from the image capturing apparatus 101), and obtaining resolution performance information about a resolution performance of the optical apparatus (para. 0025, e.g., the image capturing apparatus 105 captures a supervisory image for learning a parameter to be used for estimation processing for increasing the resolution of the image obtained by image capturing of the image capturing apparatus 101); and
generating an output image by reducing a sampling pitch of the captured image based on the captured image and the resolution performance information (para. 0026, e.g., the image processing apparatus 102 may generate a plurality of processed images by performing resolution increase processing for each of a plurality of images based on image capturing by the plurality of image capturing apparatuses 101 to 107; para. 0034, e.g., Based on the weight parameter obtained by learning, a resolution increase unit 310 increases the resolution of a low-resolution input image 505 to output an output image 506, and increases the resolution of a low-resolution input image 507 to output an output image 508),
wherein the information indicating the resolution performance is a map, and each pixel of the map indicates the resolution performance of a corresponding pixel of the captured image (para. 0031, e.g., in a learning type resolution increase method, a plurality of pairs of high-resolution supervisory images and deteriorated images obtained by reducing the resolutions of the supervisory images are prepared, and a function of mapping the supervisory image and the deteriorated image is learned; para. 0034, e.g., the resolution of a captured supervisory image is reduced to obtain a deteriorated image. Next, the learning unit 309 is made to learn a function of mapping the low-resolution deteriorated image and the high-resolution supervisory image. A parameter of a neural network obtained as a result of learning will be referred to as a weight parameter hereinafter. FIG. 5 shows, as pairs of deteriorated images and supervisory images, a pair of a deteriorated image 501 and a supervisory image 502 and a pair of a deteriorated image 503 and a supervisory image 504 ).
As to claim 2, Kokura discloses the image processing method according to claim 1, wherein the output image is an image obtained by enlarging or demosaicing the captured image (para. 0053, 0057, e.g., the resolution increase unit 310 inputs the input data pair (the pair of the input image and the resolution of the object) obtained by the association unit 307 to the neural network set with the learned weight parameter, and generates and outputs a corresponding high-resolution image).
As to claim 3, Kokura discloses the image processing method according to claim 1, wherein the resolution performance information includes information about a degree of blur occurring in the optical apparatus (Fig. 5, item 501, 503, para. 0034, e.g., a parameter of a neural network obtained as a result of learning will be referred to as a weight parameter hereinafter. FIG. 5 shows, as pairs of deteriorated images and supervisory images, a pair of a deteriorated image 501 and a supervisory image 502 and a pair of a deteriorated image 503 and a supervisory image 504).
As to claim 10, Kokura discloses the image processing method according to claim 1, wherein the optical apparatus includes an image sensor, and wherein the resolution performance information is obtained using information about a pixel pitch of the image sensor (para. 0025, 0026, 0027, 0034).
As to claim 14, Kokura discloses the image processing method according to claim 1, wherein in the generation of the output image, the output image is generated by inputting the captured image and the resolution performance information to a machine learning mode (Fig. 10, para. 0024, 0034,).
As to claim 16, Kokura discloses the image processing method according to claim 14, wherein the machine learning model includes one or more residual blocks (Fig. 10, para. 0060-0065, e.g., neural network inherently includes one or more residual blocks).
As to claims 18-19, these claims recite features similar to those discussed above. Therefore, they are rejected for reasons similar to those discussed above.
As to claim 20, Kokura discloses a method for producing a trained machine learning model comprising:
obtaining a first image, resolution performance information about a resolution performance corresponding to the first image, and a second image with a smaller sampling pitch than a sampling pitch of the first image (Fig. 3, items 301, 302, para. 0025, 0039);
generating an output image by inputting the first image and the resolution performance information to a machine learning model and reducing the sampling pitch of the first image (Fig. 3, item 310, para. 0034); and
updating weights of the machine learning model using the output image and the second image (para. 0034, 0037),
wherein the information indicating the resolution performance is a map, and each pixel of the map indicates the resolution performance of a corresponding pixel of the captured image (para. 0031, e.g., in a learning type resolution increase method, a plurality of pairs of high-resolution supervisory images and deteriorated images obtained by reducing the resolutions of the supervisory images are prepared, and a function of mapping the supervisory image and the deteriorated image is learned; para. 0034, e.g., the resolution of a captured supervisory image is reduced to obtain a deteriorated image. Next, the learning unit 309 is made to learn a function of mapping the low-resolution deteriorated image and the high-resolution supervisory image. A parameter of a neural network obtained as a result of learning will be referred to as a weight parameter hereinafter. FIG. 5 shows, as pairs of deteriorated images and supervisory images, a pair of a deteriorated image 501 and a supervisory image 502 and a pair of a deteriorated image 503 and a supervisory image 504).
As to claim 21, the claim recites features similar to those discussed above. Therefore, claim 21 is rejected for reasons similar to those discussed above.
As to claim 22, Kokura discloses an image processing system comprising: the image processing apparatus according to claim 19; and a control apparatus configured to communicate with the image processing apparatus (Fig. 2, para. 0026, 0028-0030),
wherein the control apparatus includes a unit configured to transmit a request for executing processing on the captured image (Fig. 2, para. 0026, 0028-0030), and
wherein the image processing apparatus includes a unit configured to execute processing on the captured image in response to the request (Fig. 2, para. 0026, 0028-0030).
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.
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.
Claim(s) 4- 7, 9, 11-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kokura (US 2020/0396415) in view of KIKUCHI (US 20250299297).
As to claim 4, Kokura is silent regarding a spread of a point spread function of the optical apparatus or a modulation transfer function of the optical apparatus.
KIKUCHI teaches wherein the resolution performance information includes information based on at least one of a spread of a point spread function of the optical apparatus or a modulation transfer function of the optical apparatus (para. 0050, 0052).
It would have been obvious to one of ordinary skill in the art to incorporate KIKUCHI’s teaching into Kokura since doing so would merely combine prior art elements according to known methods to yield predictable results, and enhance the blur processing as suggested by lower KIKUCHI at paragraph 0052)
As to claim 5, the combination of Kokura and KIKUCHI discloses the image processing method according to claim 1, wherein the resolution performance information includes different pieces of information for each pixel of the captured image (para. KIKUCHI, para. 0038) .
As to claim 6, the combination of Kokura and KIKUCHI discloses the image processing method according to claim 1, wherein the resolution performance information is a map having a number of pixels corresponding to the number of pixels of the captured image (para. KIKUCHI, para. 0038, 0039).
As to claim 7, the combination of Kokura and KIKUCHI discloses the image processing method according to claim 6, wherein a value of each pixel of the map is based on a frequency at which a modulation transfer function of the optical apparatus has a predetermined value (para. KIKUCHI, para. 0052).
As to claim 9, the combination of Kokura and KIKUCHI discloses the image processing method according to claim 1, wherein the resolution performance information is obtained using information about at least one of a type of the optical apparatus or a state of the optical apparatus in the image capturing, and wherein the state is at least one of a focal length, an F-number, or a focus distance (KIKUCHI, para. 0050).
As to claim 11, the combination of Kokura and KIKUCHI discloses the image processing method according to claim 1, wherein the output image is obtained by correcting blur in the captured image due to the optical apparatus (KIKUCHI, para. 0052, 0053).
As to claim 12, the combination of Kokura and KIKUCHI discloses the image processing method according to claim 1, wherein in the generation of the output image, the output image is generated based on the captured image, the resolution performance information, and information about noise in the captured image (KIKUCHI, para. 0058).
As to claim 13, the combination of Kokura and KIKUCHI discloses the image processing method according to claim 12, wherein the information about the noise includes at least one of information about an intensity of noise generated in the image capturing, or information about denoising executed on the captured image (KIKUCHI, para. 0080-0082).
Allowable Subject Matter
Claims 8, 15, 17 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHUOC TRAN whose telephone number is (571)272-7399. The examiner can normally be reached 9am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vu Le can be reached at 571-272-7332. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PHUOC TRAN/Primary Examiner, Art Unit 2668
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