Adaptive Temporal Compressive Sensing for Video
This work addresses video compression efficiency for real-time applications, presenting an incremental improvement by adapting existing compressive sensing methods.
The paper tackles the problem of video compression by introducing adaptive temporal compressive sensing, which adjusts the compression ratio based on scene complexity without degrading reconstruction quality, enabling real-time implementation through camera integration time manipulation.
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 real-time implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems.