KEYWORDS: Distortion, Quantization, Image compression, Wavelets, Computer programming, Wavelet transforms, Telecommunications, Signal to noise ratio, Data compression, Data communications
This paper presents an image coding method, based on wavelet
transform, where the distribution of the subband coefficients is
assumed to be generalized Gaussian. The shape factor and the standard
deviation are estimated in all subbands. A procedure of bit allocation
distributes then the available bitrate to the retained coefficients.
The multiple scale leader lattice vector quantization (MSLLVQ) has
shown its superiority compared to other structured quantization
schemes and now we propose its use for the quantization of the wavelet
coefficients. The main contribution of the paper is the procedure for
selecting the structure and the leaders for the MSLLVQ. An iterative
construction of the MSLLVQ scheme is presented along with the
derivation of the operational rate-distortion function. The
bit allocation procedure is based on the exponential fitting of the
operational rate-distortion curve. The results in terms of
peak signal to noise ratio are compared to other image codecs from the
literature, the advantage of such a coding structure being
particularly important for the fixed rate encoding.
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