Abstract
In this paper, an image compression method based on a weight model was proposed, which allows one to estimate the significance of the detailing coefficients of the orthogonal multiple-scale wavelet transform in terms of their contribution to the total image energy. The method presupposes the decomposition of the original image into a given number of levels, construction of significance maps for the detailing coefficients of each level, and coding of the significant coefficients. The proposed method also allows for progressive compression and restoration of images, as well as for the possible parallel software and hardware implementation. The latter is of great practical importance for reducing the time spent on image analysis and making control decisions in the systems operating in real time. The software implementation of the proposed method in a high-level language is described, which made it possible to reduce the volume of standard test halftone images by at least six times.
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