Rishi Gupta

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We propose a framework for compressive sensing of images with local geometric features. Specifically, let x &#8712; R<sup>N</sup> be an N-pixel image, where each pixel p has value x<sub>p</sub>. The image is acquired by computing the <i>measurement vector</i> Ax, where A is an m x N measurement matrix for some m l N. The goal is then to design the matrix(More)
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A, for m n, such that for any x, given Ax, we can recover a k-sparse approximation(More)
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