RUN LENGTH CODING WITH CONTEXT MODEL FOR IMAGE COMPRESSION USING SPARSE DICTIONARIES

摘要

Apparatus and methods for coding images geometric vector quantization (GVQ) having an over-complete dictionary which produces a sparse vector of coefficients as it contains large runs of zeros. The sparse encoding is particularly well suited for use with run-length entropy coding techniques. Image blocks are sparse coded using GVQ, with the vector of coefficients converted to RUN-LENGTH symbols, and binarized into a set of binary symbols. At least a portion of the binary symbols are used as contexts which can be selected when performing binary arithmetic coding of the binary coded RUN and LENGTH data to generate a bit stream containing the encoded image that provides enhanced compression.