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ICIP
1998
IEEE
13 years 11 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
DCC
2010
IEEE
14 years 2 months ago
Block Compressed Sensing of Images Using Directional Transforms
Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously wi...
Sungkwang Mun, James E. Fowler
ICIP
2006
IEEE
14 years 9 months ago
Low-Rate Reduced Complexity Image Compression using Directionlets
The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth...
Vladan Velisavljevic, Baltasar Beferull-Lozano, Ma...
GECCO
2005
Springer
177views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving next generation signal compression and reconstruction transforms via genetic algorithms
Ongoing research has established a new methodology for using genetic algorithms [2] to evolve forward and inverse transforms that significantly reduce quantization error in recons...
Frank W. Moore, Patrick Marshall
ICIP
2007
IEEE
14 years 1 months ago
Incorporating Primal Sketch Based Learning Into Low Bit-Rate Image Compression
This paper proposes an image compression approach, in which we incorporate primal sketch based learning into the mainstream image compression framework. The key idea of our approa...
Yang Li, Xiaoyan Sun, Hongkai Xiong, Feng Wu