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A layered approach to the integration of lossy and lossless image compression

 
: Marpe, D.

Tabatabai, A.:
Picture Coding Symposium '99 : April 21 - 23, 1999, Portland Hilton, Portland, Oregon
Davis: University of California, 1999
S.141-145
Picture Coding Symposium <1999, Portland/Or.>
Englisch
Konferenzbeitrag
Fraunhofer HHI ()
data compression; image coding; image reconstruction; image representation; rate distortion theory; search problems; transform coding; wavelet transformation; lossy image compression; lossless image compression; wavelet-based image coding; two-layered approach; integer wavelet packet transforms; image residual; search algorithm; rate-distortion performance; psnr

Abstract
We propose a wavelet-based image coding scheme allowing lossless and lossy compression, simultaneously. Our two-layered approach picks up the best of two worlds: it uses a high-performing wavelet-based coding technique for lossy compression in the low bit range as a first stage. For the second (optional) stage we extend the concept of reversible integer wavelet transforms to the more flexible class of integer wavelet packet transforms which allows the generation of a whole library of bases from which a best representation for a given residual between the reconstructed lossy compressed image and the original image is chosen using a fast search algorithm. We present experimental results revealing that our compression algorithm yields a rate-distortion performance similar or superior to the best currently published pure lossy still image coding methods. At the same time, the lossless compression performance of our two-layered scheme matches those of state-of-the-art pure lossless image coding schemes. Compared to other proposed lossy/lossless coding algorithms our method achieves a considerable gain in PSNR of 0.4-2.5 db for lossy reconstructions of typical images at typical rates, while simultaneously the corresponding lossless compression ratios are quite competitive.

: http://publica.fraunhofer.de/dokumente/N-13030.html