IMAGE COMPRESSION BY CARDINALITY DISTRIBUTION

Abstract

Cardinality distribution is an efficient technique to display images with different gray level systems. In this paper, we extend the application of cardinality distribution to image compression. Image is first quantized to an image with fewer gray levels. Because the cardinality-distributed images possess the desired dithering patterns, the quantized images have the more compact forms. In the decompression, gray level expansion by cardinality distribution is proposed to reconstruct the images. Therefore, cardinality distribution not only has the ability to quantize images with different gray levels but also has the potential to compress images.