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 .
Status of Claims
Currently, claims 14-19, 21-27 and 29-32 are pending in the application. Claims 14, 22, 25 , 30 and 31 are amended. Claims 20 , 28 & 33-36 are cancelled.
Response to Arguments / Amendments
Applicant’s arguments have been fully considered, but they are not persuasive, see discussion below.
Rejections under 35 U.S.C. § 103:
The applicant argued that Barron does not, in fact, disclose, teach, or suggest that the indication that is encoded "comprises a number of non-zero prediction coefficients as a sparsity number" as recited in amended independent claim 14
As to the above argument, Barron discloses indication comprises a number of non-zero prediction coefficients as a sparsity number applying design matrix for which codewords are linear combinations of not more than a specified number L of columns of X. The message is specified by the selection of columns (or equivalently by the selection of which coefficients of the linear combination are non-zero ([0110]) and plurality of the coefficients having a zero value, the number non-zero being denoted L and the value B=N/L controlling the extent of sparsity ( [0166], 1.3 Decoding Sparse Superposition Codes; Claim 4).
It should be further noted that Applicant has not presented any specific arguments with regards to the rejections of the dependent claims.
Accordingly, Examiner maintains the rejection with regards to above arguments.
Claim Rejections - 35 USC § 103
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.
Claims 14-19, 21-27 and 29-32 are rejected under 35 U.S.C. 103 as being unpatentable over LIN et al. (US 20190342546, hereinafter LIN) in view of Pace et al. (US 20150124874, hereinafter Pace) and Bivolarsky et al. (US 20110206119, hereinafter Bivolarsky) and Barron et al. (US 20130272444, hereinafter Barron)
Regarding Claim 14, LIN discloses a method, comprising:
obtaining sample values of a target area in a picture to be encoded; obtaining sample values of a regressor area in a picture to be encoded ([0044], FIG. 3, At block 32, the intra prediction unit 22221 selects a prediction mode of the block unit from a plurality of linear modes; [0046], FIG. 3, FIG. 4B, block 33, selecting a reference set of the block unit from a plurality of candidate sets, each including a plurality of candidate locations selected from a plurality of neighboring locations neighboring to the block unit);
determining at least one set of prediction coefficients [prediction model] by means of a linear regression ([0045], FIG. 3, a cross-component linear model (CCLM) prediction mode and a multiple models linear model (MMLM) prediction mode & intra prediction unit 22221 uses use more than one linear model to predict the block unit, when the prediction mode is the MMLM prediction mode; [0055], estimating the predicted parameter α and the constant parameter β based on the chroma reference samples and the luma down-sampled samples via a statistical method such as a linear regression analysis);
predicting the sample values of the target area using the determined at least one set of prediction coefficients [prediction model] to result in a first predicted sample values ([0033], perform intra-predictive coding of a current block unit relative to one or more neighboring blocks in the same frame as the current block unit & specify the location of reference samples selected from the neighboring blocks within the current frame;[0060], FIG. 3, block 36, the intra prediction unit 22221 reconstructs the block unit of the image frame based on the derived at least one linear model; [0061]);
determining best performing set of prediction coefficients [prediction model] ([0056] , derive a plurality of linear models for the block unit, when the number of the at least one model prediction is greater than one such as deriving two linear models for the block unit, when the number of the at least one model prediction is equal to two);
predicting the sample values of the target area using the best performing set of prediction coefficients [prediction model] ([0057] , at least one threshold value may be equal to a first average estimated based on all of the luma down-sampled samples, when the number of the at least one model prediction is equal to two & the at least one threshold value may be equal to a second average estimated based on all of the luma reference samples, when the number of the at least one model prediction is equal to two);
encoding an indication indicating the best performing set of prediction coefficients [prediction model] or other parameters indicating active coefficients along a bitstream ([0175] At block 96, the encoder module 812 [ fig. 8] encodes the model flag and the reference index into a bitstream; [0176], the encoder module 812 generates the bitstream including the model flag and the reference index of the block unit for providing the bitstream to the destination device 12 in FIG. 1. that includes the mode index of the block unit, when the intra prediction units 812 selects one of the intra candidate modes as the chroma prediction mode), and
iterating the steps for all target areas in the picture to be encoded ([0048], [0049], FIG. 4, repeating the encoding process to all coding blocks).
LIN does not explicitly disclose performing set of prediction coefficients [prediction model] based on [the] previously determined sets of coefficients stored in a predictor library and wherein the previously determined sets of coefficients were obtained for encoding of past target areas
Pace teaches of prediction coefficients [prediction model] based on [the] previously determined sets of coefficients stored in a predictor library ([0019], using the feature model library in decoding the unrelated or target videos such as personal, "smart" model libraries, differential libraries, and predictive libraries - modified to handle a variety of demand scenarios; [0107], re-using feature information within a model-based compression framework (MBCF) for improving the compression of another "target" video to be encoded and directly saving feature information into files, databases or data stores represents the simplest form of a feature model library that organizes and catalogs the feature information from one or more input videos)
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of previously determined sets of coefficients stored in a predictor library as taught by Pace ([0019]) into the encoding system of LIN in order to provide systems for improved inter-prediction, while maintaining the same general processing flow and framework as conventional encoders (Pace, [0017]).
LIN & Pace do the previously determined sets of coefficients were obtained for encoding of past target areas,
Bivolarsky teaches the previously determined sets of coefficients were obtained for encoding of past target areas ([0017], for each of a plurality of target ones of said image portions to be encoded, determining a respective reference portion represented by a respective set of transform domain coefficients, determining a prediction of the target image portion based on the reference portion; [0083], FIG. 5A,; Claim 1).
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of previously determined sets of coefficients were obtained for encoding of past target areas as taught by Bivolarsky ([0019]) into the encoding system of LIN & Pace in order to provide extraction of existing blocks to a global group to reduce a bitrate and greatly reduce the complexity of handling scaling and rotation type prediction (Bivolarsky, [0015]).
LIN in view of Pace and Bivolarsky does not explicitly discloses wherein the indication comprises a number of non-zero prediction coefficients as a sparsity number.
Barron teaches wherein the indication comprises a number of non-zero prediction coefficients as a sparsity number ([0110], design matrix for which codewords are linear combinations of not more than a specified number L of columns of X. The message is specified by the selection of columns (or equivalently by the selection of which coefficients of the linear combination are non-zero; [0166], 1.3 Decoding Sparse Superposition Codes; Claim 4, plurality of the coefficients having a zero value, the number non-zero being denoted L and the value B=N/L controlling the extent of sparsity)
Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of signaling a number of non- zero prediction coefficients as a sparsity number as taught by Barron ([0110]) into the encoding system of LIN , Pace and Bivolarsky in order to provide fast and reliable sparse superposition encoder for efficiently encoding transmitted digital information and exponentially decrease the probability of error (Barron, [0010]).
Regarding Claim 15, LIN in view of Pace, Bivolarsky and Barron discloses the method according to claim 14, LIN discloses wherein the target area is a set of sample values covering spatially equal areas at an encoder and a decoder in a color component ([0048], FIG. 4B, candidate locations in the first candidate set that includes the first chroma neighboring location 431 and the third chroma neighboring location 433 and the neighboring locations in the selected candidate set a plurality of reference locations for the block unit, when the reference set is selected from the candidate set;[0141], determine an intra-prediction mode directing toward reconstructed sample neighboring to the current block unit to encode the current block unit; [0068] FIG. 5, )
Regarding Claim 16, LIN in view of Pace and Bivol Bivolarsky and Barron arsky discloses the method according to claim 14, LIN discloses wherein the regressor area is a set of sample values covering spatially equal areas at an encoder and a decoder in one or more color components([0048], FIG. 4B, candidate locations in the first candidate set that includes the first chroma neighboring location 431 and the third chroma neighboring location 433 and the neighboring locations in the selected candidate set a plurality of reference locations for the block unit, when the reference set is selected from the candidate set; [0141], determine an intra-prediction mode directing toward reconstructed sample neighboring to the current block unit to encode the current block unit ).
Regarding Claim 17, LIN in view of Pace Bivolarsky and Barron discloses the method according to claim 14, LIN discloses further comprising: deciding size and shape of the target area; and deciding size, shape and location of the regressor area ([0049], FIG. 4A, each of a plurality of first location heights of the first, second, fifth, and sixth luma neighboring locations 421-422 and 425-426, and the first and second chroma neighboring locations 431-432 may be equal to a plurality of first location widths of the third, fourth, seventh, and eighth luma neighboring location 423-424 and 427-428, and the third and fourth chroma neighboring locations 433-434).
Regarding Claim 18, LIN in view of Pace Bivolarsky and Barron discloses the method according to claim 14, LIN discloses wherein the best performing set of prediction coefficients [prediction model] is determined from said at least one set of prediction coefficients [prediction model] ([0045], FIG. 3, a cross-component linear model (CCLM) prediction mode and a multiple models linear model (MMLM) prediction mode & intra prediction unit 22221 uses use more than one linear model to predict the block unit, when the prediction mode is the MMLM prediction mode; [0067]).
Regarding Claim 19, LIN in view of Pace Bivolarsky and Barron discloses the method according to claim 18, LIN discloses wherein the linear regression for a picture component is inherited from another picture component ([0080], estimate the predicted parameters α.11, α.12, . . . , and α.1N and the constant parameters β.11, β.12, . . . , and β.1N based on the chroma reference samples and the luma down-sampled samples in each of the sample groups via a linear regression analysis and a first one of the predicted parameters α.11 and a first one of the constant parameters β.11 may be derived based on two of the luma down-sampled samples and two of the chroma reference samples in a first one of the sample groups).
Regarding Claim 21, LIN in view of Pace Bivolarsky and Barron discloses the method according to claim 14, LIN discloses wherein the best performing set of coefficients is determined from the predictor library storing past sets of coefficients ([0039], the decoded picture buffer 2226 may be a reference picture memory that stores the reference block for use in decoding the bitstream by the prediction process unit 2222, e.g., in inter-coding modes).
Regarding Claims 22-27 & 29 Apparatus claims 22-27 & 29 of using the corresponding method claimed in claims 14-19 & 21, and the rejections of which are incorporated herein for the same reasons as used above.
Regarding Claim 30, Decoding Method claim 30of using the corresponding encoding method claimed in claim 14, and the rejections of which are incorporated herein for the same reasons as used above.
Regarding Claim 31, Apparatus claim 31 of using the corresponding method claimed in claim 30, and the rejections of which are incorporated herein for the same reasons as used above.
Regarding Claim 32, LIN in view of Pace Bivolarsky and Barron discloses the method according to claim 14, LIN discloses wherein the predictor library comprises a plurality of causal linear predictors comprising a cross-component correlation of a historical image or a video frame ([0045], FIG. 3, a cross-component linear model (CCLM) prediction mode and a multiple models linear model (MMLM) prediction mode & intra prediction unit 22221 uses use more than one linear model to predict the block unit, when the prediction mode is the MMLM prediction mode;[0018] )
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Samuel D Fereja whose telephone number is (469)295-9243. The examiner can normally be reached 8AM-5PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, DAVID CZEKAJ can be reached at (571) 272-7327. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SAMUEL D FEREJA/Primary Examiner, Art Unit 2487