Election/Restrictions
Applicant’s election without traverse of Species I in the reply filed on 10/27/2025 is acknowledged.
DETAILED ACTION
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(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, 8-9 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Panetta ( US 20240062530).
Regarding claim 1, Panetta teaches A method for enhancing an input image using a dual-stage image enhancement network, comprising the steps of:
generating locally-enhanced image data based on an input image( 406 in FIG.6A) using a local enhancement network ( C1 and E1, C2 and E2, …, in FIG. 6A) as a part of a first stage, wherein the local enhancement network includes a local image encoder that generates local enhancement data that indicates one or more image enhancement techniques to apply to a local region of the input image; and
generating globally-enhanced image data based on the locally-enhanced image data using a global enhancement network( 414 in FIG. 6A) as a part of a second stage, wherein the global enhancement network includes a plurality of global feature subnetworks(402 and 404 in FIG.6A), and wherein each of the global feature subnetworks is configured to draw attention to a different aspect of the locally-enhanced image data([H,W] … [H/8,W/8] in FIG 6A).
Regarding claim 2, Panetta teaches the method of claim 1, wherein the local image encoder generates a degradation profile for each of a plurality of regions of the input image, wherein the degradation profile indicates the one or more image enhancement techniques to apply to the local region of the input image([0010], the discriminative features define a portion of information about the exposure-adjusted image and an entirety of the exposure-adjusted image, integrating first ones of the discriminative features to determine a type of scene, subjects in the scene, and/or lighting conditions, and second ones of the discriminative features represent local texture or object at a given location in the exposure-adjusted image, employing a feature condense network and a feature enhance network to determine the local and global features) .
Regarding claim 3, Panetta teaches the method of claim 2, wherein each degradation profile specifies one or more degradation type-value items, wherein each degradation type-value item specifies a degradation type for a degradation and a degradation value that indicates an associated value or flag representing an extent or presence of the degradation ( [0078]-[0080], the LXT can map the low-intensity values to a broader range of values while compressing the range of higher intensity values. Conversely, to obtain the under-exposed images I′U, the inverse LXT function can expand the higher intensity regions and compress the range of lower intensities. Different contrast gains can be utilized for different regions by incorporating the local standard deviation of a region. This method is presented as the LSDACE, where D is a constant and the contrast gain is inversely proportional to the local standard deviation and is also spatially adaptive).
Regarding claim 8, Panetta teaches the method of claim 1, wherein the global image encoder and the global image decoder form a convolutional neural network( Fig. 6A).
Regarding claim 9, Panetta teaches the method of claim 8, wherein the global image encoder and the global image decoder include skip connections( [0073], the system 400 can include skip connections between the feature condense network 402 and the feature enhance network 404).
Allowable Subject Matter
Claim 7 is 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 JIANGENG SUN whose telephone number is (571)272-3712. The examiner can normally be reached 8am to 5pm, EST, M-F.
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JIANGENG SUN
Examiner
Art Unit 2661
/Jiangeng Sun/Examiner, Art Unit 2671
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