Title :
Color satellite image compression using the evidence theory and Huffman coding
Author :
Sahnoun, Khaled ; Benabadji, Noureddine
Author_Institution :
Dept. of Phys., Univ. of Sci. & Technol. of Oran (USTOMB), El M´nouar, Algeria
Abstract :
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.
Keywords :
Huffman codes; data compression; decoding; image coding; image colour analysis; vectors; Huffman coding; code vector; color satellite image compression technique; decoding; encoding; evidence theory; k-nearest neighbor algorithm; quantization step; vector quantization; Huffman coding; Image coding; Image color analysis; Satellites; Support vector machine classification; Vector quantization; Huffman coding; Vector quantization; compression; evidence theory; k-nearest neighbor;
Conference_Titel :
Computer and Information Technology (WCCIT), 2013 World Congress on
Conference_Location :
Sousse
Print_ISBN :
978-1-4799-0460-0
DOI :
10.1109/WCCIT.2013.6618755