Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A communication system and the method of operation thereof includes: a block size unit for receiving an input digital data stream; a progressive-Golomb encoder, coupled to the block size unit, for encoding a progressive-Golomb codeword from the input digital data stream; and a transmitter unit, coupled to the progressive-Golomb encoder for transferring the progressive-Golomb codeword to an output device.

Abstract: 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.

Abstract: Implementations generally relate to data-charge phase data compression. In one implementation, a method includes computing prediction values for image data, where the image data is data-charge phase data, and where the computing of prediction values is based on inter-block prediction. The method also includes computing residual data based on the prediction values. The method also includes quantizing the residual data. The method also includes entropy encoding the quantized residual data. The method also includes refining an inverse quantized residual data based on one or more of the residual data and a number of left-over bit-budget after entropy encoding.

Abstract: Implementations generally relate to pre-charge phase data compression. In some implementations, a method includes computing prediction values for image data, where the image data is pre-charge phase data. The method also includes computing residual data based on the prediction values. The method also includes quantizing the residual data. The method also includes entropy encoding the quantized residual data. The method also includes refining an inverse quantized residual data based on one or more of the residual data and a number of left-over bit-budget after entropy encoding.

Abstract: Implementations generally relate to data-charge phase data compression. In one implementation, a method includes computing prediction values for image data, where the image data is data-charge phase data, where the computing of prediction values is based on inter-block prediction, and where an additional bit-budget is assigned to a first block of the image data. The method also includes computing residual data based on the prediction values. The method also includes quantizing the residual data. The method also includes entropy encoding the quantized residual data. The method also includes refining an inverse quantized residual data based on one or more of the residual data and a number of left-over bit-budget after entropy encoding.

Abstract: 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.

Abstract: 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.

Abstract: Implementations generally relate to pre-charge phase data compression. In some implementations, a method includes computing prediction values for image data, where the image data is pre-charge phase data. The method also includes computing residual data based on the prediction values. The method also includes quantizing the residual data. The method also includes entropy encoding the quantized residual data. The method also includes refining an inverse quantized residual data based on one or more of the residual data and a number of left-over bit-budget after entropy encoding.

Abstract: Implementations generally relate to data-charge phase data compression. In one implementation, a method includes computing prediction values for image data, where the image data is data-charge phase data, where the computing of prediction values is based on inter-block prediction, and where an additional bit-budget is assigned to a first block of the image data. The method also includes computing residual data based on the prediction values. The method also includes quantizing the residual data. The method also includes entropy encoding the quantized residual data. The method also includes refining an inverse quantized residual data based on one or more of the residual data and a number of left-over bit-budget after entropy encoding.

Abstract: Implementations generally relate to data-charge phase data compression. In one implementation, a method includes computing prediction values for image data, where the image data is data-charge phase data, and where the computing of prediction values is based on inter-block prediction. The method also includes computing residual data based on the prediction values. The method also includes quantizing the residual data. The method also includes entropy encoding the quantized residual data. The method also includes refining an inverse quantized residual data based on one or more of the residual data and a number of left-over bit-budget after entropy encoding.

Abstract: An apparatus and method for performing variable length coding (VLC) within an adaptive entropy image coding process are presented. VLC is performed using a progressive coding technique, such as progressive Golomb coding (PGC) whose operation is based on a set of parameters. Grouping is performed within image distribution contexts, such as number of quantized bit planes (qn), previous residual, predictor type, and color, so that each group having similar contexts is associated with a set of progressive coding parameters. The grouping can be performed on-line or off-line. In operation, the progressive coding parameters then change in response to changing image distribution contexts toward optimizing image coding, such as increasing peak signal-to-noise ratio (PSNR).

Abstract: Apparatus and method for optimizing encoding and decoding when using embedded block coding, in which each block is independent coded is described. Instead of coding the whole block in response to a single mode decision, the block is separated into multiple sub-blocks sharing the same block bit budget. A block is divided for example in response to color or spatial considerations. A joint mode decision is then made where mode (DPCM/PCM) as well as qn are independently determined for each sub-block, while optimizing the use of the overall bit budget by sharing bits between the sub-blocks through refinement bits.

Abstract: An apparatus and method for enhanced encoding and decoding of Bayer images is presented. The use of intra-plane prediction, which relies on correlation between neighboring pixels of the same color, is enhanced by adding inter-plane prediction that relies on correlation between neighboring pixels in different color planes (i.e., different colors). The inter-plane prediction is performed within either a single residual computation, or across multiple residual computations, such as generating an intra-predicted set of residuals which are then utilized in computing inter-predicted residuals.