This paper addresses the image representation problem in visual sensor networks. We propose a new image representation scheme based on compressive sensing (CS) because compressive...
An image reconstruction algorithm using compressed sensing (CS) with deterministic matrices of second-order ReedMuller (RM) sequences is introduced. The 1D algorithm of Howard et ...
We present a framework for segmenting and storing filament networks from scalar volume data. Filament structures are commonly found in data generated using high-throughput microsc...
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...
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...