文章基本信息

标题：Sparsity Properties of Compressive Video Sampling Generated by Coefficient Thresholding
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作者：Ida Wahidah Hamzah ; Tati Latifah R. Mengko ; Andriyan B. Suksmono 等
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2014
卷号：12
期号：4
页码：897-904
DOI：10.12928/telkomnika.v12i4.296
语种：English
出版社：Universitas Ahmad Dahlan
摘要：We study the compressive sampling (CS) and its application in video encoding framework. The video input is firstly transformed into suitable domain in order to achieve sparser configuration of coefficients. Then, we apply coefficient thresholding to classify which frames to be sampled compressively or conventionally. For frames chosen to undergo compressive sampling, the coefficient vectors will be projected into smaller vectors using random measurement matrix. As CS requires two main conditions, i.e. sparsity and matrix incoherence, this research is emphasized on the enhancement of sparsity property of the input signal. It was empirically proven that the sparsity enhancement could be reached by applying motion compensation and thresholding to the non-significant coefficient count. At the decoder side, the reconstruction algorithm can employ basis pursuit or L1 minimization algorithm.