Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients

By Juan Liu, Pierre Moulin. IEEE Transactions on Image Processing, 2001

297 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/20322c1287506c7493f90e5fd4aebeac111d61cf

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In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

Iterative Gaussianization: From ICA to Random Rotations (2011, methodology): “To do this, images were transformed using orthonormal QMF wavelet domain with four frequency scales [49], an then each subband was converted to patches in order to obtain different PDF models for each subband according to well-known properties of natural images in wavelet domains [12], [50].”
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency (2002, background): “In addition, [28] presents an information-theoretic analysis of statistical dependencies between wavelet coefficients.”
Image Quality Assessment: From Error Measurement to Structural Similarity (2004, background): “It has been shown that a strong dependency exists between intra-and interchannel wavelet coefficients of natural images [36], [37].”
Modern Image Quality Assessment (2006, background): “It has been empirically shown that a strong dependency exists between the intra- and interchannel wavelet coefficients of natural images [40, 41].”
Directional multiscale modeling of images using the contourlet transform (2006, methodology): “DEPENDENCE CHARACTERIZATION VIA INFORMATION-THEORETIC ANALYSIS In this section, we quantitatively study the joint statistics of contourlet coefficients in complement to the qualitative study in the previous section, using mutual information as a measure of dependencies [23].”
Image quality assessment: from error visibility to structural similarity (2004, unknown): “It has been shown that a strong dependency exists between intra- and inter-channel wavelet coefficients of natural images [36],[37].”
SAR speckle reduction using wavelet denoising and Markov random field modeling (2002, unknown): “[38] J. Liu and P. Moulin, “Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients,”IEEE Trans.”
41 OBJECTIVE VIDEO QUALITY ASSESSMENT (2003, background): “It has been shown that a strong correlation or dependency exists between intra- and inter-channel wavelet coefficients of natural images [60,61].”