Color satellite image compression using the evidence theory and Huffman coding

The color satellite image compression technique by vector quantization can be improved either by acting directly on the step of constructing the dictionary or by acting on the quantization step of the input vectors. In this paper, an improvement of the second step has been proposed. The k-nearest neighbor algorithm was used on each axis separately. The three classifications, considered as three independent sources of information, are combined in the framework of the evidence theory. The best code vector is then selected, after the image is quantized, Huffman schemes compression is applied for encoding and decoding.