Multiresolution support applied to image filtering and restoration
Graphical Models and Image Processing
Generalized cross validation for wavelet thresholding
Signal Processing
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
A Fast Algorithm for Deblurring Models with Neumann Boundary Conditions
SIAM Journal on Scientific Computing
Wavelets and curvelets for image deconvolution: a combined approach
Signal Processing - Special section: Security of data hiding technologies
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Shearlet-based total variation diffusion for denoising
IEEE Transactions on Image Processing
Wavelet-based statistical signal processing using hidden Markovmodels
IEEE Transactions on Signal Processing
ForWaRD: Fourier-wavelet regularized deconvolution for ill-conditioned systems
IEEE Transactions on Signal Processing
Data compression and harmonic analysis
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Wavelet shrinkage and generalized cross validation for image denoising
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
The curvelet transform for image denoising
IEEE Transactions on Image Processing
Deconvolution by thresholding in mirror wavelet bases
IEEE Transactions on Image Processing
An EM algorithm for wavelet-based image restoration
IEEE Transactions on Image Processing
A spatially adaptive nonparametric regression image deblurring
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
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
Texas Two-Step: A Framework for Optimal Multi-Input Single-Output Deconvolution
IEEE Transactions on Image Processing
A Fast Thresholded Landweber Algorithm for Wavelet-Regularized Multidimensional Deconvolution
IEEE Transactions on Image Processing
Deblurring Using Regularized Locally Adaptive Kernel Regression
IEEE Transactions on Image Processing
Image deconvolution using incomplete Fourier measurements
International Journal of Imaging Systems and Technology
Hi-index | 0.02 |
In this paper, a new type of deconvolution algorithm is proposed that is based on estimating the image from a shearlet decomposition. Shearlets provide a multidirectional and multiscale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets. Constructions such as curvelets and contourlets share similar properties, yet their implementations are significantly different from that of shearlets. Taking advantage of unique properties of a new M-channel implementation of the shearlet transform, we develop an algorithm that allows for the approximation inversion operator to be controlled on a multiscale and multidirectional basis. A key improvement over closely related approaches such as ForWaRD is the automatic determination of the threshold values for the noise shrinkage for each scale and direction without explicit knowledge of the noise variance using a generalized cross validation (GCV). Various tests show that this method can perform significantly better than many competitive deconvolution algorithms.