We propose a framework for compressive sensing of images with local geometric features. Specifically, let x ∈ RN be an N-pixel image, where each pixel p has value xp. The image...
Rishi Gupta, Piotr Indyk, Eric Price, Yaron Rachli...
—This paper addresses the problem of simultaneous signal recovery and dictionary learning based on compressive measurements. Multiple signals are analyzed jointly, with multiple ...
Jorge Silva, Minhua Chen, Yonina C. Eldar, Guiller...
We reduce transmission bandwidth and memory space for images by factoring their repeated content. A transform map and a condensed epitome are created such that all image blocks ca...
We generalize our results of [8, 9] and propose a new framework of multitree dictionaries which include many previously proposed dictionaries as well as many new, very large, tree...
Yan Huang, Ilya Pollak, Minh N. Do, Charles A. Bou...
Compressive sampling (CS), or “Compressed Sensing,” has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively...