TY - GEN
T1 - Compressive imaging for superresolution from a single exposure
AU - Stern, Adrian
AU - Rivenson, Yair
AU - Javidi, Bahram
PY - 2010/11/17
Y1 - 2010/11/17
N2 - Superresolution is typically achieved by taking multiple slightly different exposures. Here we present a superresolution technique that requires only a single exposure. Inspired by the compressive sensing approach that takes advantage of the information redundancy in typical images we show that true superresolution is feasible from a single exposure. The single shot superresolution system is based on the well known double random phase encoding setup which was broadly investigated for its encryption purposes. It is shown that combining double random phase encoding imaging with a compressive sensing based reconstruction technique, can super-resolve both diffraction and geometrical limited resolution imaging.
AB - Superresolution is typically achieved by taking multiple slightly different exposures. Here we present a superresolution technique that requires only a single exposure. Inspired by the compressive sensing approach that takes advantage of the information redundancy in typical images we show that true superresolution is feasible from a single exposure. The single shot superresolution system is based on the well known double random phase encoding setup which was broadly investigated for its encryption purposes. It is shown that combining double random phase encoding imaging with a compressive sensing based reconstruction technique, can super-resolve both diffraction and geometrical limited resolution imaging.
UR - https://www.scopus.com/pages/publications/78149446335
U2 - 10.1109/WIO.2010.5582488
DO - 10.1109/WIO.2010.5582488
M3 - Conference contribution
AN - SCOPUS:78149446335
SN - 9781424482276
T3 - 2010 9th Euro-American Workshop on Information Optics, WIO 2010
BT - 2010 9th Euro-American Workshop on Information Optics, WIO 2010
T2 - 2010 9th Euro-American Workshop on Information Optics, WIO 2010
Y2 - 12 July 2010 through 16 July 2010
ER -