DETAILED ACTION
Claims 1-7 and 11-14 are pending for examination.
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 .
Priority
Acknowledgment is made of applicant's claim under CN 202210837739 filed on 7/15/2022.
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.
Claim(s) 1, 6, 7 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al, US 2016/0154994 A1, in view of Wu et al, US 2007/0201751 A1.
Regarding Claim 1, Kim discloses an image encoding method, comprising: acquiring an original image and performing image patching to obtain a plurality of image patches; calculating gradient values of pixels in each of the image patches (Kim [0061] – The SIFT may indicate a vector obtained by dividing an adjacent image patch into 4×4 blocks, calculating a histogram associated with a gradient orientation and magnitude of pixels included in each block, and connecting bin values of the histogram)
However, Kim does not explicitly disclose screening out key area patches from the plurality of image patches according to the gradient values of the pixels; and performing encoding by inputting the key area patches and position information of the key area patches in the original image into a vision transformation model to generate a bit stream
Wu teaches screening out key area patches from the plurality of image patches according to the gradient values of the pixels; and performing encoding by inputting the key area patches and position information of the key area patches in the original image into a vision transformation model to generate a bit stream (Wu [0018]-[0019] – Encoder 112 calculates gradients 122 and generates gradient histogram(s) 124 for each block 120 to identify statistical characteristics for each block. To generate gradients 122 for a block 120, encoder 112 calculates 8 directional gradients for each non-boundary pixel in the block 120. To determine distributions of gradient values, encoder 112 thresholds (independent of gradient direction) the gradients 122 for a block 120 to classify and group gradients 122; FIG. 2 shows an exemplary set of gradient histograms 124, according to one embodiment. In these examples, horizontal coordinates represent pixel gray values (e.g., 0-255), and vertical coordinates represent pixels counts. For example, when gradient of a pixel is low, then the count of low gradient at the pixel gray value increases one..Based on the gradient distributions exhibited by each block 120, encoder 112 classifies the block 120 as a smooth, text, hybrid, or picture block type. A histogram 124 representing a smooth block type will typically exhibit only low gradient pixels and show one peak corresponding to a low-gradient class pixel distribution; [0039] – At block 606, encoder 112 selects a particular encoding algorithm to encode the block 120 based on quality parameters associated with the block type, a total rate constraint, and acceptable distortion. At block 608, encoder 112 encodes each block 120 of the digital image 114 based on the corresponding selected encoding algorithm to generate a compressed image 116).
Therefore, it 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 to modify Kim to determine key area patches and encoding the key patches, as taught by Wu. One would be motivated as using the histogram to determine certain features and encoding said features based on the histogram.
With regard to claim 6, the claim limitations are essentially the same as claim 1 but in a different embodiment. Therefore, the rational used to reject claim 1 is applied to claim 6.
With regard to claim 7, the claim limitations are essentially the same as claim 1 but in a different embodiment. Therefore, the rational used to reject claim 1 is applied to claim 7.
Allowable Subject Matter
Claims 2-5 and 11-14 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.
The following is a statement of reasons for the indication of allowable subject matter:
The various claimed limitations mentioned in the claims are not taught or suggested by the prior art taken either singly or in combination, with emphasize that it is each claim, taken as a whole, including the interrelationships and interconnections between various claimed elements make them allowable over the prior art of record. The various claimed limitations mentioned including the interrelationships and all of the limitations of the base claim and the elements with respect to
calculating the gradient values of pixels in each of the image patches, and calculating an average gradient value of each of the image patches according to the gradient values of the pixels; and sorting the plurality of image patches according to the average gradient value, and determining image patches for which the average gradient value is not less than a preset value among the plurality of image patches as the key area patches
inputting the key area patches into the vision transformation model, and outputting encoded visible patches and mask tokens; and generating image tokens according to the encoded visible patches, the mask tokens and the position information of the key area patches in the original image, and generating the bit stream according to the image tokens
acquiring the original image having a size of n x n, wherein n is a positive integer; and evenly partitioning the original image having the size of n x n into m x m patches according to non-overlapping areas, to obtain the image patches each of which has a size of n/m X n/m, wherein m is a positive integer, and n >m
discarding the image patches for which the average gradient value is smaller than a preset value among the plurality of image patches; wherein the preset value is set so that the number of the discarded image patches and a preset compression ratio a of the image satisfy the following formula found in claims 5 and 14
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMIR SHAHNAMI whose telephone number is (571)270-0707. The examiner can normally be reached Monday - Friday 8:00 am to 4:00 pm.
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/AMIR SHAHNAMI/ Primary Examiner, Art Unit 2483