DocumentCode :
3706272
Title :
Compressed sensing block-wise exposure control algorithm using optical flow estimation
Author :
Tao Xiong;Jie Zhang;Sang Chin;Trac D. Tran;Ralph Etienne-Cummings
Author_Institution :
Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
fYear :
2015
Firstpage :
1
Lastpage :
4
Abstract :
Recently, CMOS image sensors have attracted more and more attention from the applications of navigation, monitoring and search-and-rescue operations. Specially, CMOS image sensors mounted on insects need to be fast, adaptive to the environment and power efficiency. To simultaneously satisfy both requirements of reconstruction quality and low power consumption, we propose a compressed sensing block-wise exposure control algorithm using optical flow estimation. This framework has been demonstrated to further improve recovery performance (> 25 dB) with high compression ratio (>= 10 : 1), which also provides a promising method for real-time CMOS implementation.
Keywords :
"Optical imaging","Optical sensors","Compressed sensing","Estimation","Image reconstruction","Biomedical optical imaging"
Publisher :
ieee
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE
Type :
conf
DOI :
10.1109/BioCAS.2015.7348443
Filename :
7348443
Link To Document :
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