Abstract

An image coding scheme using the discrete cosine transform is analyzed when the transform coefficients are vector quantized. The coding method is based on the known scheme proposed by Chen and Smith (1977) which sorts the picture blocks into classes according to the level of image activity. The coding scheme is modified to allow for vector quantization of the ac coefficients, in particular a pyramid vector quantizer (PVQ) is used. This is based on the statistical and geometric properties of a Laplacian source which, in fact, is the best model for the ac coefficients of the two-dimensional discrete cosine transform (2D-DCT) of an image. A method for forming almost statistically independent vectors is also suggested and improves quantization performance. Images are encoded with both the PVQ and standard scalar quantizer transform coders, demonstrating that the PVQ coder reduces the mean square encoding error and improves image quality. In particular, emphasis is given to how the use of fractional bit rates affects the objective and subjective gains obtained. The results presented (i.e. mean square error values and printed images) have been obtained experimentally, working with a statistical criterion in a group of images whose size was in accordance with the 50 Hz CCIR Recommendation 601 Standard.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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