Recent trends in compression of multispectral imagery

We provide a comprehensive trade-off analysis of major compression algorithms as applied to multispectral imagery. Our goal is to identify a real-time, low cost codec for multispectral imagery. Hence the major criteria used for performance and ranking of various algorithms emphasize implementation complexity in addition to compression performance and robustness. Multispectral imagery codecs are designed by suitably extending and modifying the state-of-art still image codecs so that the resultant codec simultaneously benefits from the spatial and spectral correlations inherent in multispectral imagery. In particular, two different approaches of interest which emerge are vector quantization (VQ) and transform coding (TC). This paper describes and analyzes some recently developed multispectral imagery codecs utilizing the above two approaches. For completeness, a brief overview of alternate approaches is also included