Compressed sensing or compressive sampling (CS) has been receiving a lot of interest as a promising method for signal recovery and sampling. CS problems can be cast as convex prob...
Seung-Jean Kim, Kwangmoo Koh, Michael Lustig, Step...
Compressive sensing is the reconstruction of sparse images or signals from very few samples, by means of solving a tractable optimization problem. In the context of MRI, this can ...
Vector representation of binary images has an advantage of keeping high image quality for arbitrary scaling as well as editing capability of an object. However, the vector represe...
This paper deals with the optimization of a new technique of image compression. After the wavelet transform of an image, blocks of coefficients are further linearly decomposed us...
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....