Title :
Progressive compressive imaging by single-pixel imager
Author :
Zelong Wang ; Jubo Zhu ; Fengxia Yan
Author_Institution :
Dept. of Math. & Syst. Sci., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
The progressive compressive imaging by single-pixel imager is presented in this paper. We aim to offer the online control of the tradeoff between the sampling rate and the quality of the recovered image and avoid the need of a priori knowledge of the object sparsity. Moreover, we can implement the proposed approach by the innovation method to reduce the computation complexity and the memory requirements as well as improving the recovery precision. We also show the stopping rule and the finite truncation for the innovation method. The results in the numerical simulations show the feasibility of the proposed method.
Keywords :
computational complexity; image sampling; numerical analysis; computation complexity; finite truncation; memory requirements; numerical simulations; object sparsity; progressive compressive imaging; recovered image; sampling rate; single-pixel imager; stopping rule; Complexity theory; Compressed sensing; Image coding; Numerical simulation; Optical imaging; Technological innovation; Compressive imaging; Progressive imaging; finite truncation; innovation method; single-pixel imager; stopping rule;
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
DOI :
10.1109/ICSPCC.2013.6663919