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journal article·2020-11-01Open access

Reconstruction of compressed video via non-convex minimization

Chao Ji, Jinshou Tian, Liang Sheng, Kai He, Liwei Xin, Xin Yan, Yanhua Xue, Minrui Zhang, Ping Chen, Xing Wang

AIP Advances· Volume 10· Issue 11
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Source abstract

Abstract

This paper studies the sparsity prior to compressed video reconstruction algorithms. An effective non-convex 3DTPV regularization (0 < p < 1) is proposed for sparsity promotion. Based on the augmented Lagrangian reconstruction algorithm, this paper analyzes and compares three non-convex proximity operators for the ℓp-norm function, and numerous simulation results confirmed that the 3DTPV regularization can gain higher video reconstruction quality than the existing convex regularization and is more competitive than the existing video reconstruction algorithms.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Sparse and Compressive Sensing Techniques · Advanced Image Processing Techniques · Image and Signal Denoising Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Ultra-fast Photoelectric Diagnostics Technology, Xi’an Institute of Optics and Precision Mechanics (XIOPM), Chinese Academy of Sciences (CAS) 1 , Xi’an, Shaanxi 710119, China

University of Chinese Academy of Sciences 2 , Beijing 100049, China

Collaborative Innovation Center of Extreme Optics, Shanxi University 3 , 92 Wucheng road, Taiyuan 030006, Shanxi, China

The Northwest Institute of Nuclear Technology 4 , Xi’an 710024, China

State Key Laboratory of Transient Optics and Photonics, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences 5 , Xi’an, Shaanxi 710119, China

Funding

Scientific Instrument Developing Project of the Chineses Academy of Sciences · Youth Program of National Natural Science Foundation

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