Compressive sensing with local geometric features

Compressive sensing with local geometric features

We propose a framework for compressive sensing of images with local geometric features. Specifically, let x ∈ R[superscript N] be an N-pixel image, where each pixel p has value x[subscript p]. The image is acquired by computing the measurement vector Ax, where A is an m x N measurement matrix for so...

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Bibliographic Details
Main Authors: Gupta, Rishi V. (Contributor), Indyk, Piotr (Contributor), Price, Eric C. (Contributor), Rachlin, Yaron (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery (ACM), 2012-09-17T18:00:43Z.
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