This paper deals with the Bayesian signal denoising problem, assuming a prior based on a sparse representation modeling over a unitary dictionary. It is well known that the maximum...
This paper exploits the interband correlations of color and multispectral images for wavelet-based denoising. For this, a multispectral extension of the linear minimum mean square...
With the recent availability of commercial light field cameras, we can foresee a future in which light field signals will be as common place as images. Hence, there is an immine...
Kernel regression is an effective tool for a variety of image processing tasks such as denoising and interpolation [1]. In this paper, we extend the use of kernel regression for de...
Super-resolution (SR) is the process of combining multiple aliased low-quality images to produce a high-resolution high-quality image. Aside from registration and fusion of low-res...
M. Dirk Robinson, Cynthia A. Toth, Joseph Y. Lo, S...