Sparse representations using overcomplete dictionaries are used in a variety of field such as pattern recognition and compression. However, the size of dictionary is usually a tra...
Recent work has demonstrated that using a carefully designed dictionary instead of a predefined one, can improve the sparsity in jointly representing a class of signals. This has m...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
The surface reflectance function of many common materials varies slowly over the visible wavelength range. For this reason, linear models with a small number of bases (5-8) are fr...
Recent work has demonstrated that using a carefully designed sensing matrix rather than a random one, can improve the performance of compressed sensing. In particular, a welldesign...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...