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Compressed Sensing-Based Distributed Image Compression
AbstractIn this paper, a new distributed block-based image compression method based on the principles of compressed sensing (CS) is introduced. The coding and decoding processes are performed entirely in the CS measurement domain. Image blocks are classified into key and non-key blocks and encoded at different rates. The encoder makes use of a new adaptive block classification scheme that is based on the mean square error of the CS measurements between blocks. At the decoder, a simple, but effective, side information generation method is used for the decoding of the non-key blocks. Experimental results show that our coding scheme achieves better results than existing CS-based image coding methods.
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Baig, M.Y.; Lai, E.M.-K.; Punchihewa, A. Compressed Sensing-Based Distributed Image Compression. Appl. Sci. 2014, 4, 128-147.View more citation formats
Baig MY, Lai EM-K, Punchihewa A. Compressed Sensing-Based Distributed Image Compression. Applied Sciences. 2014; 4(2):128-147.Chicago/Turabian Style
Baig, Muhammad Y.; Lai, Edmund M.-K.; Punchihewa, Amal. 2014. "Compressed Sensing-Based Distributed Image Compression." Appl. Sci. 4, no. 2: 128-147.