Title :
Adaptive temporal compressive sensing for video
Author :
Xin Yuan ; Jianbo Yang ; Llull, Patrick ; Xuejun Liao ; Sapiro, Guillermo ; Brady, David J. ; Carin, Lawrence
Author_Institution :
Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
Abstract :
This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene´s temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to realtime implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems.
Keywords :
compressed sensing; image reconstruction; natural scenes; video cameras; video coding; adaptive temporal compressive sensing; camera integration time; compressed data; compression ratio; generalized temporal CS approach; hardware systems; scene temporal complexity; video reconstruction; Cameras; Compressed sensing; Motion measurement; Noise measurement; PSNR; Streaming media; Velocity measurement; Video compressive sensing; adaptive temporal compressive sensing; real-time implementation; temporal compressive sensing ratio design; temporal superresolution;
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
DOI :
10.1109/ICIP.2013.6738004