In this paper, a novel scheme for low-power image coding and decoding based
on vector quantization is presented. The proposed scheme uses small codebo
oks, and block transformations are applied to the codewords during coding.
Using small codebooks, the proposed scheme has reduced memory requirements
in comparison to classical vector quantization. The transformations applied
to the codewords extend computationally the small codebooks compensating f
or the quality degradation introduced by the small codebook size. Thus the
coding task becomes computation-based rather than memory-based, leading to
significant power savings since memory-related power consumption forms the
major part of the total power consumption of a system. Since the parameters
or the transformations depend on the image block under coding, the small c
odebooks are dynamically adapted to the specific block under coding leading
to acceptable image qualities. The proposed scheme leads to power savings
of a factor of 10 in coding and of a factor of 3 in decoding, at least in c
omparison to classical full-search vector quantization. The main factor aff
ecting both image quality and power consumption is the size of the codebook
that is used.