Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present ...
In this paper, we first present a survey of existing color buffer compression algorithms. After that, we introduce a new scheme based on an exactly reversible color transform, si...
Jim Rasmusson, Jon Hasselgren, Tomas Akenine-M&oum...
The Balanced Subgraph problem (edge deletion variant) asks for a 2-coloring of a graph that minimizes the inconsistencies with given edge labels. It has applications in social netw...
A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
Jeffrey D. Blanchard, Coralia Cartis, Jared Tanner...
We address the problem of exact signal recovery in frequency domain optical coherence tomography (FDOCT) systems. Our technique relies on the fact that, in a spectral interferomet...
S. Chandra Sekhar, Rainer A. Leitgeb, Martin L. Vi...