Image denoising with anisotropic bivariate shrinkage

Authors:
Songfeng Yin;Liangcai Cao;Yongshun Ling;Guofan Jin
Affiliations:
State Key Lab of Precision Measurement Technology and Instruments, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, China and Key Lab of Infrared and Low T ...;State Key Lab of Precision Measurement Technology and Instruments, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, China;Key Lab of Infrared and Low Temperature Plasma of Anhui Province, Electronic Engineering Institute, Hefei 230037, China;State Key Lab of Precision Measurement Technology and Instruments, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, China
Venue:
Signal Processing
Year:
2011

Citing 22
Cited 4

Hidden Markov tree modeling of complex wavelet transforms

ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01
Image/video denoising based on a mixture of Laplace distributions with local parameters in multidimensional complex wavelet domain

Signal Processing
Image denoising with an optimal threshold and neighbouring window

Pattern Recognition Letters
Image denoising in steerable pyramid domain based on a local Laplace prior

Pattern Recognition
Shape adaptive estimation of variance in steerable pyramid domain and its application for spatially adaptive image enhancement

ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Image denoising with neighbour dependency and customized wavelet and threshold

Pattern Recognition
A New Wavelet-based image denoising using undecimated discrete wavelet transform and least squares support vector machine

Expert Systems with Applications: An International Journal
Image denoising in contourlet domain based on a normal inverse Gaussian prior

Digital Signal Processing
Complex Gaussian scale mixtures of complex wavelet coefficients

IEEE Transactions on Signal Processing
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency

IEEE Transactions on Signal Processing
Wavelet-based statistical signal processing using hidden Markovmodels

IEEE Transactions on Signal Processing
Noise Covariance Properties in Dual-Tree Wavelet Decompositions

IEEE Transactions on Information Theory
De-noising by soft-thresholding

IEEE Transactions on Information Theory
Adaptive wavelet thresholding for image denoising and compression

IEEE Transactions on Image Processing
Wavelet-based image estimation: an empirical Bayes approach using Jeffrey's noninformative prior

IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain

IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation

IEEE Transactions on Image Processing
Estimating the probability of the presence of a signal of interest in multiresolution single- and multiband image denoising

IEEE Transactions on Image Processing
The Nonsubsampled Contourlet Transform: Theory, Design, and Applications

IEEE Transactions on Image Processing
A New SURE Approach to Image Denoising: Interscale Orthonormal Wavelet Thresholding

IEEE Transactions on Image Processing
Pointwise Shape-Adaptive DCT for High-Quality Denoising and Deblocking of Grayscale and Color Images

IEEE Transactions on Image Processing
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering

IEEE Transactions on Image Processing

Symmetric self-Hilbertian filters via extended zero-pinning

Signal Processing
Using anisotropic bivariate threshold function for image denoising in NSCT domain

IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
A new class of almost symmetric orthogonal Hilbert pair of wavelets

Signal Processing
Sharper Symmetric Self-Hilbertian wavelets

Signal Processing

Quantified Score

Hi-index	0.08

Visualization

Abstract

This paper presents a novel image denoising algorithm based on the modeling of wavelet coefficients with an anisotropic bivariate Laplacian distribution function. The anisotropic bivariate Laplacian model not only captures the child-parent dependency between wavelet coefficients, but also fits the anisotropic property of the variances of wavelet coefficients in different scales of natural images. With this statistical model, we derive a closed-form anisotropic bivariate shrinkage function in the framework of Bayesian denoising and a new image denoising approach with local marginal variance estimation based on this newly derived shrinkage function is proposed in the discrete wavelet transform (DWT) domain. The proposed anisotropic bivariate shrinkage approach is also extended to the dual-tree complex wavelet transform (DT-CWT) domain to further improve the performance of image denoising. To take full advantage of DT-CWT, a more accurate noise variance estimator is proposed and the way the anisotropic bivariate shrinkage function applied to the magnitudes of DT-CWT coefficients is presented. Experiments were carried out in both the DWT and the DT-CWT domain to validate the effectiveness of the proposed method. Using a representative set of standard test images corrupted by additive white Gaussian noise, the simulation results show that the proposed method provides promising results and is competitive with the best wavelet-based denoising results reported in the literature both in terms of peak signal-to-noise ratio (PSNR) and in visual quality.