EFFICIENT COMPRESSIVE SENSING VIDEO COMPRESSION METHOD BASED ON GAUSSIAN MIXTURE MODELS

被引：0

作者：

Li, Xiangwei ^{[1
]}

Lan, Xuguang ^{[1
]}

Yang, Meng ^{[1
]}

Xue, Jianru ^{[1
]}

Zheng, Nanning ^{[1
]}

机构：

[1] Xi An Jiao Tong Univ, Inst Artificial Intelligence & Robot, Xian 710049, Peoples R China

来源：

2016 30TH ANNIVERSARY OF VISUAL COMMUNICATION AND IMAGE PROCESSING (VCIP) | 2016年

关键词：

compressive sensing video; Gaussian mixture model; lossy compression;

D O I：

暂无

中图分类号：

TB8 [摄影技术];

学科分类号：

0804 ;

摘要：

In this paper, we propose an efficient lossy compression method for the compressive sensing video that utilizes Gaussian mixture models (GMM). The GMM is used to model the compressive sensing video (CSV) frames. Then we design an efficient lossy compression method based on the GMM. Each CSV frame can be efficiently compressed by the proposed method. The proposed method is for better compromise of compression efficiency and computational complexity. And it achieves a significant Bjontegaard-Delta (BD)-PSNR improvement about 8.84 similar to 41.81dB in average compared with existing low complexity compression solutions for compressing the CSV sequence.

引用

页数：4

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