A novel interpolative vector quantization scheme

Abstract

Abstract A novel adaptive interpolative vector quantization scheme is developed and presented in this paper. Instead of constructing an approximation of the original image with the traditional fix-rate subsampling and interpolation process, a new dominant point detection algorithm is employed to build a non-uniformly spaced decimation lattice. In effect, better approximation and lower bit-rate are achieved by extracting only those sampling points which have significant effects on the aliasing error. The difference between the original and the approximated image is encoded with vector quantization . Experimental results show that the decoded images are found to exhibit coding fidelity of over 34 dB with improved visual quality over existing vector quantization techniques. A comparison of the proposed scheme with other existing methods of similar complexity has also been presented.