Subspace reference neighbourhood search and its application in image coding

This paper presents a new searching method, the Subspace Reference Neighbourhood Search (SRNS), to reduce the computational requirement in encoding image so that only a small number of distance calculations is needed to locate the closest codeword in a codebook and, at the same time, to preserve a good image quality. One significant advantage of this method is that the reference codeword can be located directly from the algorithm. The performances of SRNS in simulated known data sources and practical images are discussed and analyzed