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JEI
2008
100views more  JEI 2008»
13 years 4 months ago
Context adaptive image denoising through modeling of curvelet domain statistics
We perform a statistical analysis of curvelet coefficients, distinguishing between two classes of coefficients: those that contain a significant noise-free component, which we call...
Linda Tessens, Aleksandra Pizurica, Alin Alecu, Ad...
PR
2010
184views more  PR 2010»
13 years 3 months ago
Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images
The total variation-based image denoising model has been generalized and extended in numerous ways, improving its performance in different contexts. We propose a new penalty func...
Aditya Chopra, Heng Lian
ICIP
1998
IEEE
13 years 9 months ago
Spatially Adaptive Wavelet Thresholding with Context Modeling for Image Denoising
The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on ...
S. Grace Chang, Bin Yu, Martin Vetterli
SSPR
2004
Springer
13 years 10 months ago
Adaptive Context for a Discrete Universal Denoiser
Abstract. Statistical analysis of spatially uniform signal contexts allows Discrete Universal Denoiser (DUDE) to effectively correct signal errors caused by a discrete symmetric me...
Georgy L. Gimel'farb
TIP
2008
163views more  TIP 2008»
13 years 4 months ago
Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation. Neighborhoods are modeled as ...
David K. Hammond, Eero P. Simoncelli