The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Multichannel Deconvolution
Journal of Mathematical Imaging and Vision
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Frequency analysis and sheared reconstruction for rendering motion blur
ACM SIGGRAPH 2009 papers
Multiresolution image representation using combined 2-D and 1-D directional filter banks
IEEE Transactions on Image Processing
A shearlet approach to edge analysis and detection
IEEE Transactions on Image Processing
Full length article: Compactly supported shearlets are optimally sparse
Journal of Approximation Theory
Multiresolution direction filterbanks: theory, design, and applications
IEEE Transactions on Signal Processing - Part I
FIR perfect signal reconstruction from multiple convolutions: minimum deconvolver orders
IEEE Transactions on Signal Processing
A filter bank for the directional decomposition of images: theoryand design
IEEE Transactions on Signal Processing
Spatially adaptive wavelet thresholding with context modeling for image denoising
IEEE Transactions on Image Processing
The curvelet transform for image denoising
IEEE Transactions on Image Processing
Gray and color image contrast enhancement by the curvelet transform
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
Multidimensional Multichannel FIR Deconvolution Using GrÖbner Bases
IEEE Transactions on Image Processing
The Nonsubsampled Contourlet Transform: Theory, Design, and Applications
IEEE Transactions on Image Processing
A New Family of Nonredundant Transforms Using Hybrid Wavelets and Directional Filter Banks
IEEE Transactions on Image Processing
Critically Sampled Wavelets With Composite Dilations
IEEE Transactions on Image Processing
Windowed Spectral Regularization of Inverse Problems
SIAM Journal on Scientific Computing
Hi-index | 0.00 |
It is widely recognized that the performance of many image processing algorithms can be significantly improved by applying multiscale image representations with the ability to handle very efficiently directional and other geometric features. Wavelets with composite dilations offer a flexible and especially effective framework for the construction of such representations. Unlike traditional wavelets, this approach enables the construction of waveforms ranging not only over various scales and locations but also over various orientations and other orthogonal transformations. Several useful constructions are derived from this approach, including the well-known shearlet representation and new ones, introduced in this paper. In this work, we introduce and apply a novel multiscale image decomposition algorithm for the efficient digital implementation of wavelets with composite dilations. Due to its ability to handle geometric features efficiently, our new image processing algorithms provide consistent improvements upon competing state-of-the-art methods, as illustrated on a number of image denoising and image enhancement demonstrations.