The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Given a color image previously compressed using JPEG, we estimate the image's JPEG compression history components including the color transformation, subsampling, and the qua...
Ramesh Neelamani, Ricardo L. de Queiroz, Zhigang F...
Many technical imaging applications, like coding "images" of digital elevation maps, require extracting regions of compressed images in which the pixel values are within...
An application of compressive sensing (CS) theory in imagebased robust face recognition is considered. Most contemporary face recognition systems suffer from limited abilities to ...
Mergers are procedures that, with the aid of a short random string, transform k (possibly dependent) random sources into a single random source, in a way that ensures that if one ...