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- W4312253285 abstract "For the forward interframe reconstruction of video compressive sensing, the existing algorithms derive their residual sparse models by multihypothesis prediction from a forward keyframe or a previous non-keyframe. However, these algorithms simply fix the quantity of hypothesis candidates during successive approximation of each non-keyframe. Therefore, this paper proposes an iterative progressive-hypothesis prediction algorithm which provides a hypothesis descent prior for the multihypothesis prediction. The proposed algorithm alternately implements the prior-guided patch matching and prediction-based residual sparse modelling to improve the recovery quality of each non-keyframe. By introducing a coarse-to-fine hypothesis selection mechanism, the proposed algorithm can obtain higher matching accuracy for the interframe multihypothesis. As compared with other interframe reconstruction algorithms, the proposed algorithm can achieve good recovery quality under the low-delay reconstruction framework." @default.
- W4312253285 created "2023-01-04" @default.
- W4312253285 creator A5054991316 @default.
- W4312253285 creator A5088664989 @default.
- W4312253285 date "2022-09-26" @default.
- W4312253285 modified "2023-10-16" @default.
- W4312253285 title "Iterative Progressive-hypothesis Prediction for Forward Interframe Reconstruction of Video Compressive Sensing" @default.
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- W4312253285 doi "https://doi.org/10.1109/mmsp55362.2022.9949468" @default.
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