Sony Corporation

Apple Inc.

Fastvdo LLC

Hye-Yeon Cheong

Ali Jezu Tabatabai

Alexandros Michael Tourapis

David William Singer

Masaru Ikeda

Pankaj N Topiwala

Mohammed Golam Sarwer

Dominik Mehlem

Yoichi Yagasaki

Mohammad Gharavi-Alkhansari

Takefumi Nagumo

Alexis Michael Tourapis

A system comprises an encoder configured to compress video data using an in-loop noise generation process that generates noise in the compression loop at a sub-image portion level of granularity, such as at a block level. The encoder includes noise model and/or noise model input parameter information in an encoded bit stream. Also, a system includes a decoder configured to receive such a bit stream and decompress the video using an in-loop noise generation process that generates noise in the decompression loop at a sub-image portion level of granularity.

Video compression with in-loop sub-image level controllable noise generation

A system comprises an encoder configured to compress media objects using a compression loop that includes a residual decomposition component that decomposes a residual signal for a block of the media object being compressed into multiple sub-error signals. The encoder is further configured to enable different transformation and/or quantization processes to be specified to be applied to different ones of the sub-errors. A corresponding decoder is configured to apply inverse transformation/quantization processing to the sub-error signals, based on the transformation/quantization processes that were applied at the encoder. The decoder then re-creates a residual signal from the processed sub-error signals and uses the re-created residual signal to correct predicted values at the decoder.

Media object compression/decompression with adaptive processing for block-level sub-errors and/or decomposed block-level sub-errors

A system includes an encoder configured to compress media objects using a compression loop that includes a residual decomposition component that decomposes a residual signal for a block of the media object being compressed into multiple sub-error signals. The encoder is further configured to enable different transformation and/or quantization processes to be specified to be applied to different ones of the sub-errors. A corresponding decoder is configured to apply inverse transformation/quantization processing to the sub-error signals, based on the transformation/quantization processes that were applied at the encoder. The decoder then re-creates a residual signal from the processed sub-error signals and uses the re-created residual signal to correct predicted values at the decoder.

An image-processing apparatus to compress digital image data, includes a memory that stores a digital image in a first storage space. The image-processing apparatus further includes one or more image-processing circuits that selects a block from a plurality of blocks of the digital image. A plurality of encoded blocks is generated by application of a plurality of sequential encoding schemes on the selected block. One encoded block is detected from the generated plurality of encoded blocks that has a maximum bit-coverage value. A sequential encoding scheme is selected from the plurality of sequential encoding schemes as an optimal sequential encoding scheme. The selected sequential encoding scheme is associated with the detected encoded block with the maximum bit-coverage value. The selected block of the digital image is converted to a compressed bit stream storable in a reduced second storage space in the memory, by use of the sequential encoding scheme.

Apparatus and method for image compression based on optimal sequential encoding scheme

A media device includes a processor to calculate a value of an objective function for each sequence of modes of a plurality of sequences of modes, based on at least statistical data of a plurality of modes. The plurality of sequences of modes corresponds to different combinations of modes from the plurality of modes. The plurality of modes corresponds to a plurality of encoding operations executed. The processor selects a sequence of modes from the plurality of sequences of modes based on a value of the objective function associated with the sequence of modes. The modes in the selected sequence of modes are less than the plurality of modes and represents an optimal encoding scheme executable to encode an input image block.

Image coding modes selection for an embedded codec circuitry

To improve encoding efficiency, residual values are mapped so that only non-negative values are utilized when performing the encoding process.

Residual mapping method for image/video compression

An embedded codec (EBC) circuitry includes encoder circuitry to determine a count of bits required to encode a plurality of quantized prediction residual levels in each sub-block of a plurality of sub-blocks of an image block, for a first coding scheme and a second coding scheme. The encoder circuitry allocates a bit value to a signaling bit for each sub-block of the plurality of sub-blocks, based on the determined count of bits. A value of the signaling bit represents either the first coding scheme or the second coding scheme. The encoder circuitry generates a bit-stream of the image block by selective application of either the first coding scheme or the second coding scheme on each sub-block of the plurality of sub-blocks, based on the value allocated to the signaling bit for each sub-block of the plurality of sub-blocks.

Embedded codec circuitry for sub-block based encoding of quantized prediction residual levels

An embedded codec (EBC) circuitry includes encoder circuitry to determine a refinement start position in a bit-plane of an encoded data block based on a random number. The refinement start position is a position in the bit-plane based on a value of the random number. The encoder circuitry determines a refinement order in the bit-plane for refining un-coded bits present in the bit-plane, based on the determined refinement start position and a refinement step size. The refinement order is a sequence of positions of the un-coded bits in the bit-plane that will be refined in that sequence. The encoder circuitry refines the un-coded bits by allocating a refinement bit at the refinement start position in the bit-plane and then followed by the allocation of subsequent refinement bits in the determined refinement order.

Embedded codec circuitry for randomized refinement of uncoded-bits

An embedded codec (EBC) circuitry includes encoder circuitry to encode a plurality of sub-blocks of an image block by an entropy coding scheme to generate a plurality of encoded data blocks. Each encoded data block includes a first plurality of bit-planes and a second plurality of bit-planes. The first plurality of bit-planes include a plurality of entropy coded bits. The encoder circuitry determines a count of refinement bits of a plurality of refinement bits, for an encoded data block of the plurality of encoded data blocks, based on a quality measure of the plurality of encoded data blocks. The quality measure represents a count of the plurality of entropy coded bits in each encoded data block. The encoder circuitry allocates the count of refinement bits in the second plurality of bit-planes of the encoded data block.

Embedded codec circuitry for visual quality based allocation of refinement bits

An image-processing apparatus and method for quantization partitioning for enhanced image compression, includes storage of an input image in a first storage space having a first storage access bandwidth. The image-processing apparatus selects a plurality of QP values from a defined QP range for a first block of a plurality of blocks of the input image. The plurality of QP values are selected from the defined QP range based on defined criteria. The image-processing apparatus is configured to encode, by the selected plurality of QP values, the first block to generate an encoded bit stream of the first block. The encoded bit stream of the first block is storable in a reduced second storage space in the memory with a reduced second storage access bandwidth.

Quantization partitioning for enhanced image compression

A sub-block entropy coding method more efficiently encodes content. Specifically, by selecting the most optimal tables for each sub-block, the number of bits utilizes is minimized. Furthermore, based on results, tables are able to be eliminated as options to further reduce the number of signaling bits.

Sub-block based entropy coding for image coding

Embedded codec (EBC) circuitry for frequency-dependent coding of transform coefficients, groups a plurality of transform coefficients for an input image block into a plurality of groups of transform coefficients. The plurality of transform coefficients are grouped based on a frequency distribution of the plurality of transform coefficients for the input image block. The EBC circuitry selects a different entropy coding parameter from a set of entropy coding parameters for each group of the plurality of groups, based on the frequency distribution. Thereafter, the EBC circuitry applies an entropy coding scheme from a set of entropy coding schemes to each group of transform coefficients, in accordance with the selected entropy coding parameter.

Embedded codec circuitry and method for frequency-dependent coding of transform coefficients

To improve intra coding prediction, cross-color prediction utilizes spatial correlation and cross-color correlation to generate a more accurate predictor. Cross-color prediction is also able to be used in a dynamic system which selects between cross-color prediction and intra-color prediction.

Cross color prediction for image/video compression

A solution is provided to estimate motion vectors of a video. A multistage motion vector prediction engine is configured to estimate multiple best block-matching motion vectors for each block in each video frame of the video. For each stage of the motion vector estimation for a block of a video frame, the prediction engine selects a test vector form a predictor set of test vectors, computes a rate-distortion optimization (RDO) based metric for the selected test vector, and selects a subset of test vectors as individual best matched motion vectors based on the RDO based metric. The selected individual best matched motion vectors are compared and a total best matched motion vector is selected based on the comparison. The prediction engine selects iteratively applies one or more global matching criteria to the selected best matched motion vector to select a best matched motion vector for the block of pixels.

Growing community of inventors

Los Gatos, CA, United States of America

Hye-Yeon Cheong