Modeling the Joint Statistics of Images in the Wavelet Domain

E P Simoncelli

Published in Proc SPIE, 44th Annual Meeting, vol.3813 pp. 188--195, Jul 1999.
© SPIE, 1999

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  • 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.
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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.: AbstractRandom cascades on wavelet trees and their use in modeling and analyzing natural imagery
    by M J Wainwright, E P Simoncelli, and A S Willsky
  • 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.: AbstractImage compression via joint statistical characterization in the wavelet domain
    by R W Buccigrossi and E P Simoncelli
  • 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.: AbstractAdaptive Wiener Denoising Using a Gaussian Scale Mixture Model in the Wavelet Domain
    by J Portilla, V Strela, M J Wainwright, and E P Simoncelli
  • 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.: AbstractA parametric texture model based on joint statistics of complex wavelet coefficients
    by J Portilla and E P Simoncelli
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