A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
The steerable pyramid: a flexible architecture for multi-scale derivative computation
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A Non-Local Algorithm for Image Denoising
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Unsupervised, Information-Theoretic, Adaptive Image Filtering for Image Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image denoising with neighbour dependency and customized wavelet and threshold
Pattern Recognition
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency
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IEEE Transactions on Signal Processing
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
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IEEE Transactions on Signal Processing
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Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors
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Shiftable multiscale transforms
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De-noising by soft-thresholding
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Image compression via joint statistical characterization in the wavelet domain
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Adaptive wavelet thresholding for image denoising and compression
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IEEE Transactions on Image Processing
Wavelet-based image estimation: an empirical Bayes approach using Jeffrey's noninformative prior
IEEE Transactions on Image Processing
The curvelet transform for image denoising
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
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IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Optimal Spatial Adaptation for Patch-Based Image Denoising
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
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IEEE Transactions on Image Processing
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IEEE Transactions on Image Processing
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
IEEE Transactions on Image Processing
Image Restoration Using Space-Variant Gaussian Scale Mixtures in Overcomplete Pyramids
IEEE Transactions on Image Processing
Restoration of images corrupted by Gaussian and uniform impulsive noise
Pattern Recognition
Expert Systems with Applications: An International Journal
Image denoising in contourlet domain based on a normal inverse Gaussian prior
Digital Signal Processing
Image denoising with anisotropic bivariate shrinkage
Signal Processing
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This paper presents a new image denoising algorithm based on the modeling of coefficients in each subband of steerable pyramid employing a Laplacian probability density function (pdf) with local variance. This pdf is able to model the heavy-tailed nature of steerable pyramid coefficients and the empirically observed correlation between the coefficient amplitudes. Within this framework, we describe a novel method for image denoising based on designing both maximum a posteriori (MAP) and minimum mean squared error (MMSE) estimators, which relies on the zero-mean Laplacian random variables with high local correlation. Despite the simplicity of our spatially adaptive denoising method, both in its concern and implementation, our denoising results achieves better performance than several published methods such as Bayes least squared Gaussian scale mixture (BLS-GSM) technique that is a state-of-the-art denoising technique.