We present results quantifying the exploitability of compressed remote sensing imagery. The performance of various feature extraction and classification tasks is measured on hype...
Mihaela D. Pal, Christopher M. Brislawn, Steven P....
This work presents a Log-stable model for natural images blockvariance. Exponential and halfnormal distributions have been previously used to model block-variance, but they were e...
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...
Compressive sampling (CS), or “Compressed Sensing,” has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively...