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Abstract: Efficient coding of natural scenes requires the use of a proper filter to reduce their redundancy. In this work we show that nongaussian statistical properties of natural scenes uniquely define a wavelet filter that decomposes the image in a set of statistically independent resolution levels. The spatial statistical dependences still present at a fixed scale are extremely short-ranged. (Update)
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BibTeX entry: (Update)
@misc{ turiel-wavelet,
author = "Antonio Turiel and Néstor Parga",
title = "Wavelet Based Decomposition Of Natural Images In Independent Resolution
Levels",
url = "citeseer.ist.psu.edu/486786.html" }
Citations (may not include all citations):1526 Ten Lectures on Wavelets (context) - Daubechies - 1992
29 IEEE Transactions on Information Theory (context) - Simoncelli, Freeman et al.
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5 and Tripiccione C (context) - Benzi, Ciliberto et al. - 1993
5 Neural Computation (context) - Turiel, Parga - 2000
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1 Tang Chao (context) - Tollhurst, Tadmor - 1992
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1 Clay Reid R (context) - Dan - 1996
1 IEEE Transactions on Biomedical Engineering (context) - Daugman - 1989
1 to Network (context) - Nevado, Parga et al.
1 IEEE Trans Image Processing (context) - Buccigrossi, Simoncelli - 1999
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