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Satellite image Compression reduces redundancy in data representation in order to achieve saving in the cost of storage and transmission image compression compensates for the limited on-board resources, in terms of mass memory and downlink bandwidth and thus it provides a solution to the (bandwidth vs. data volume) dilemma of modern spacecraft Thus compression is very important feature in payload image processing units of many satellites, In this paper, an improvement of the quantization step of the input vectors has been proposed. The k-nearest neighbour (KNN) algorithm was used on each axis. 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 Huffman schemes is applied for encoding and decoding.

Satellite Image Compression Technique Based on the Evidence Theory