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For 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. [ABSTRACT FROM AUTHOR]

The authors have previously proposed a quantization scheme in which the ac discrete cosine transform coefficients after normalization are quantized by the gain/shape vector quantizer (called DCT-G/SVQ). It is shown from the relation between the quantization complexity and the S/N ratio that DCT-G/SVQ exhibits a better performance than the discrete cosine transform coding with vector quantization (called DCT-VQ) discussed in the literature [6]. This paper proposes the adaptive DCT-G/SVQ, in which the adaptive control is introduced £or the coding parameters of DCT-G/SVQ. Two methods of adaptive control are considered--the mode- selection and the recursive adaptation. The adaptive DCT-G/SVQ has a better performance than the traditional adaptive discrete cosine transform coding using the scalar quantizer. In other words, the S/N ratio is improved by 1.0 to 1.5 dB in the mode-selection adaptive control coding at the same coding rate. The S/N ratio in the recursive adaptive control coding is improved by 0.5 to 1.0 dB. The adaptive DCT-G/SVQ based on the mode-selection control exhibits nearly the same coding performance as the adaptive DCT-VQ of [9] with the same adaptive control scheme, but is superior since it requires less complexity in quantization. [ABSTRACT FROM AUTHOR]

A gain/shape vector quantizer for orthogonal transform domain has been designed based on a previous paper [11] on a gain/shape vector quantizer for a spherically symmetric random source. Such a design method is used in the design of a discrete cosine transform encoder with gain/shape vector quantizer. This encoder is similar to that described in [7] except in the following: (i) it has a gain/shape codebook; and (ii) its normalized coefficients of discrete cosine transform are modeled as having spherically symmetric distribution. The S/N rendition of this encoder is 1.0 - 2.5 dB better than that of the DCT coding scheme with Max-type scalar quantizer at the same bit rate. Furthermore, in spite of its similarity to the conventional discrete cosine transform coding scheme with vector quantizer [7], the encoder introduced in this paper delivers higher S/N using the same number of multiplications for the quantization of normalized coefficients, and/or the same amount of memory for the codebook. [ABSTRACT FROM AUTHOR]