Convex projections based edge recovery in low bit rate VQ

This paper proposes an implementation for vector quantizers (VQ) with very small codebooks (i.e., 30-32 codevectors) for compressing grayscale images. The technique uses a convex projections (CP) based algorithm for iterative restoration of edges, as part of the decoding process. The objective of this approach is to code the edge blocks vestigially by drastically reducing the number of edge vectors in a codebook. This will result in a large reduction in codebook size and hence fast searches. Also this method works better on images outside the training set since encoding is less dependent on the edges.