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 ...
Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously wi...
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...
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...
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...