Improvement on singular value decomposition vector quantization

Abstract

AbstractFor high‐efficiency image compression, previously, an SVD (singular value decomposition)‐based coder was developed using vector quantization, called SVD‐VQ. This paper proposes an improved quantization SVD‐VQ scheme. For every input subblock, the SVD‐VQ coder scalar‐quantizes a singular value and vector‐quantizes two singular vectors, separately. The SVD‐VQ decoder reproduces a subblock as the product of these quantization outputs, but does not necessarily produce a reconstruction with the minimum distortion in an image space. This paper develops a quantization scheme where the minimum‐distortion reconstruction is always provided in the original image space and presents its design algorithm. The improved SVD‐VQ shows A/N performance improvement of 0.5 ‐ 1.0 dB over the conventional SVD‐VQ, and is similar in performance to the adaptive DCT (discrete cosine transform) coder.