Multi-hypothesis compressed video sensing by two-step iterative thresholding. (2018)

• Record Type: Journal Article
• Authors: Chen, Rui; Tong, Ying; Yang, Jie; Wu, Minghu
• Is Part Of: International journal of intelligent information and database systems. Volume 11:Number 2/3(2018)
• Page Start: 207
• Page End: 224
• Publication Date: 2018
• Subjects: compressed sensing -- multi-hypothesis prediction -- distributed video coding -- DVC -- wireless sensor network -- WSN; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Traditional distributed video coding schemes achieved compression by using a single reference frame for side information, which plays a key-role in determining the performance of the codec. To refine side information, we propose a novel side information generation algorithm by using two neighbouring key frames as reference. The proposed algorithm uses multi-hypothesis predictions to fully utilise the intra and inter frame correlations. Three side information candidates are obtained by applying multi-hypothesis predictions and bi-directional motion estimation on the non-key frame and its bi-directional reference frames. The most similar candidate is chosen by calculating the correlation coefficients between the non-key frame and the three candidates. With the refined side information, the video frames are reconstructed by blocked compressed sensing with a smoothed project-landweber (BCS-SPL) algorithm. Experimental results demonstrate that the proposed algorithm outperforms the original schemes in refining the side information as well as improving the reconstruction performance.