A data compression apparatus is described which has an encoder configured to receive an input data item and to compress the data item into an encoding comprising a plurality of numerical values. The numerical values are grouped at least according to whether they relate to content of the input data item or style of the input data item. The encoder has been trained using a plurality of groups of training data items grouped according to the content and where training data items within individual ones of the groups vary with respect to the style. The encoder has been trained using a training objective which takes into account the groups.

A data compression apparatus is described which has an encoder configured to receive an input data item and to compress the data item into an encoding comprising a plurality of numerical values. The numerical values are grouped at least according to whether they relate to content of the input data item or style of the input data item. The encoder has been trained using a plurality of groups of training data items grouped according to the content and where training data items within individual ones of the groups vary with respect to the style. The encoder has been trained using a training objective which takes into account the groups.

Methods, articles, and systems of video coding use intra block copying with hash-based searches.

System and method embodiments for image coding are disclosed. In an embodiment, a method in a data processing system for image encoding includes determining a sparsity constraint according to a dimension of an input image signal. The method also includes iteratively determining a plurality of approximations to the input image signal. Each iteration provides an approximation of the input image signal. Each approximation includes a set of dictionary element indices and coefficients. The dictionary is an over-complete dictionary. Iterations of the determining step are terminated when a number of iterations is equal to the sparsity constraint. The method also includes selecting one of the plurality of approximations according to a minimum rate-distortion cost. The method also includes determining an encoded image signal according to non-zero coefficients and corresponding indices for each non-zero coefficient in the selected approximation.

System and method embodiments for image coding are disclosed. In an embodiment, a method in a data processing system for image encoding includes determining a sparsity constraint according to a dimension of an input image signal. The method also includes iteratively determining a plurality of approximations to the input image signal. Each iteration provides an approximation of the input image signal. Each approximation includes a set of dictionary element indices and coefficients. The dictionary is an over-complete dictionary. Iterations of the determining step are terminated when a number of iterations is equal to the sparsity constraint. The method also includes selecting one of the plurality of approximations according to a minimum rate-distortion cost. The method also includes determining an encoded image signal according to non-zero coefficients and corresponding indices for each non-zero coefficient in the selected approximation.

In a video coding system, an encoder may include a coding engine to predictively code input video, a decoder to reconstruct reference pictures generated by the coding engine, a reference picture cache to store the reconstructed reference pictures, a patch cache to store prediction patches generated from other sources, and a prediction search unit to search among the reference picture cache and the patch cache to generate prediction references for use by the coding engine while coding input video. The prediction patches may be assembled from a variety of sources including: predefined image content, reference pictures being evicted from the reference picture cache, image content of prior coding sessions and image data stored by applications on a common terminal where the encoder resides. A decoder may store prediction patches in its own patch cache for synchronous decoding.

In a video coding system, an encoder may include a coding engine to predictively code input video, a decoder to reconstruct reference pictures generated by the coding engine, a reference picture cache to store the reconstructed reference pictures, a patch cache to store prediction patches generated from other sources, and a prediction search unit to search among the reference picture cache and the patch cache to generate prediction references for use by the coding engine while coding input video. The prediction patches may be assembled from a variety of sources including: predefined image content, reference pictures being evicted from the reference picture cache, image content of prior coding sessions and image data stored by applications on a common terminal where the encoder resides. A decoder may store prediction patches in its own patch cache for synchronous decoding.

Implementations related to coding and/or decoding image data employing video coding with embedded motion are disclosed.

Implementations related to coding and/or decoding image data employing video coding with embedded motion are disclosed.

Methods, articles, and systems of video coding use intra block copying with hash-based searches.