Despite the popularity of wavelet-based image compression, its error inhomogeneity - the error that is different for even and odd pixel locations, has not been previously analyzed...
In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measure...
This paper presents a novel fuzzy stochastic Kalman filter for compression of digital images. In particular, it is shown that the state evolution of the synthesis coefficients of ...
We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incohe...
We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coef?cients of an arbitrary li...
Karen O. Egiazarian, Alessandro Foi, Vladimir Katk...