The total variation model of Rudin, Osher, and Fatemi for image denoising is considered to be one of the best denoising models. In the past, its solutions were based on nonlinear ...
Wavelet-domain hidden Markov models (HMMs) have been recently proposed and applied to image processing, e.g., image denoising. In this paper, we develop a new HMM, called local co...
This paper presents a new approach to demosaicing of spatially sampled image data observed through a color filter array, in which properties of Smith-Barnwell filterbanks are empl...
Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis ar...
We present a new approach based on Partial Differential Equations (PDE) to restore noisy blurred images. After studying the methods to denoise images, staying as close as possible...