Compressive domain spatial–temporal difference saliency‐based realtime adaptive measurement method for video recovery. Issue 11 (14th August 2019)

• Record Type: Journal Article
• Authors: Li, Honggui
• Is Part Of: IET image processing. Volume 13:Issue 11(2019)
• Page Start: 2008
• Page End: 2017
• Publication Date: 2019-08-14
• Subjects: data compression -- object detection -- compressed sensing -- video coding -- approximation theory; binary‐group approximation algorithm -- compressive domain spatial–temporal difference‐based saliency detection -- video restoration -- realtime adaptive CS -- adaptive compressed sensing method -- video recovery -- compressive domain spatial–temporal difference saliency‐based realtime adaptive measurement method -- compressive measurements; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2019.0116
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : This study proposes an adaptive compressed sensing (CS) method for video recovery based on spatial–temporal difference saliency in compressive domain. Firstly, the theoretical framework of realtime adaptive CS for video restoration is established, which includes two components: on‐chip and off‐chip. Secondly, the computation model of compressive domain spatial–temporal difference‐based saliency detection is built, which merely depends on the intra‐frame and inter‐frame similarities of compressive measurements. Thirdly, binary‐group approximation algorithm of subrate allocation is presented to achieve a quasi‐optimal solution. Finally, simulation experiments are designed to evaluate the performance of the proposed method, and it is indicated by the experimental results that the proposed method is suitable for realtime implementation and holds higher peak signal to noise ratio compared with the state‐of‐the‐art methods.