Abstract
A method for image compression based on subband decomposition is presented. We describe a new filter bank design method for image coding applications and a new entropy coding algorithm for the compression of subband images. A set of relevant optimization criteria is defined for the filter bank design. For the compression, a composite source model is defined by combining vector quantization (VQ) and scalar quantization (SQ) with entropy coding. In the proposed scheme, VQ exploits the remaining statistical dependencies among the subband samples, while SQ allows an optimal control on local distortions. The system is based on a statistical model that uses VQ information to generate low entropy probability tables for an arithmetic coder. The bit rate can be shared between the VQ rate and the SQ rate, allowing many possible configurations in terms of performance and implementation complexity. The proposed system shows improved performance when compared with other existing methods.
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