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Embedded image compression based on wavelet pixel classification and sorting

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2 Author(s)
Kewu Peng ; Department of Electrical and Computer Engineering, University of Minnesota, 55455, USA ; Kieffer, J.

A new embedded image compression algorithm is proposed, based on progressive Pixel Classification And Sorting (PCAS) in wavelet domain. To exploit the intraband and interband correlation in wavelet domain, EZW [1] and SPIHT [2] implicitly classify wavelet pixels as zerotree pixels or not, while MRWD[3], SLCCA[4], and EBCOT[5] implicitly classify wavelet pixels as neighbors of significant pixels or not. In this paper, the wavelet pixels to be encoded are explicitly and finely classified based on their predicted probabilities, which is more sophisticated and effective. Furthermore, wavelet pixel sorting is introduced to help improve rate-distortion performance within each bit-plane coding. The technique of pixel classification and sorting is simple, yet effective to produce the image code with excellent compression performance. In addition, our algorithm provides both SNR and resolution scalability.

Published in:

Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on  (Volume:4 )

Date of Conference:

13-17 May 2002

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