This paper proposes an extension of compressed sensing that allows to express the sparsity prior in a dictionary of bases. This enables the use of the random sampling strategy of c...
This paper presents an efficient compression-oriented segmentation algorithm for computer-generated document images. In this algorithm, a document image is represented in a block-...
This paper addresses the problem of generating a superresolution (SR) image from a single low-resolution input image. We approach this problem from the perspective of compressed s...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
Compressed sensing(CS) suggests that a signal, sparse in some basis, can be recovered from a small number of random projections. In this paper, we apply the CS theory on sparse ba...
Dikpal Reddy, Aswin C. Sankaranarayanan, Volkan Ce...
: This paper addresses the problem of reconstructing an image from 1-bit-quantized measurements, considering a simple but nonconventional optical acquisition model. Following a com...