MB-RACS: Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network

arXiv:2402.16855v1 Announce Type: new
Abstract: Conventional compressed sensing (CS) algorithms typically apply a uniform sampling rate to different image blocks. A more strategic approach could be to allocate the number of measurements adaptively, based on each image block's complexity. In this paper, we propose a Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network (MB-RACS) framework, which aims to adaptively determine the sampling rate for each image block in accordance with traditional measurement bounds theory. Moreover, since in real-world scenarios statistical information about …

abstract algorithms apply arxiv block complexity cs.cv framework image measurement network paper rate sampling sensing type uniform