I describe a statistical model for natural photographic images, when decomposed in a multi-scale wavelet basis. In particular, I examine both the marginal and pairwise joint histograms of wavelet coefficients at adjacent spatial locations, orientations, and spatial scales. Although the histograms are highly non-Gaussian, they are nevertheless well described using fairly simple parameterized density models. Warning: Undefined array key 2 in /System/Volumes/Data/e/1.3/p1/lcv/html_public/pubs/makeAbs.php on line 304
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Statistical Modeling: Random Cascades on Wavelet Trees and Their Use in Modeling and Analyzing Natural Imagery. M J Wainwright and E P Simoncelli and A S Willsky. Applied and Computational Harmonic Analysis, 11(1), 2001. In Press.: Wainwright00
Compression: Image Compression via Joint Statistical Characterization in the Wavelet Domain. R W Buccigrossi and E P Simoncelli. IEEE Trans Image Processing, 8(12):1688-1701, Dec 1999.: Buccigrossi97
Denoising: Adaptive Wiener Denoising using a Gaussian Scale Mixture Model in the Wavelet Domain. J Portilla, V Strela, M Wainwright, and E P Simoncelli. 8th IEEE Int'l Conf on Image Processing. Thessaloniki, Greece. 7-10 October 2001.: Portilla01a
Texture Modeling: A parametric texture model based on joint statistics of complex wavelet coefficients. J Portilla and E P Simoncelli. Int'l Journal of Computer Vision 40(1):49-71, October 2000.: Portilla99