基于网格编码量化的压缩感知量化问题研究  

Quantization of Compressive Sensing Based on Trellis Coded Quantization

作　　者：田彩丽[1] 方勇[1] 

机构地区：[1]西北农林科技大学信息工程学院

出　　处：《科技通报》2015年第8期265-267,共3页Bulletin of Science and Technology

基　　金：国家自然科学基金:算术码码谱及其应用研究(61271280)

摘　　要：压缩感知理论提出至今,学术界对其理论研究取得了重大的成果,并将其应用于各个领域。本文主要研究其量化方式,将网格编码量化(TCQ)方法应用于压缩感知的信号量化过程,基于压缩感知理论获取采样信号,采样信号运用网格编码量化方式量化,解码端对信号重构,重构使用2D正交匹配追踪算法。实验结果表明,该方法可以减少图像压缩时间,不影响压缩图像的质量。Compressive sensing has been applied to many areas, but the reaserch about quantizationg have less works The trellis coded quantization （TCQ） is applied to the signal quantization process of compressed sensing, The signal acquired with compressed sensing was qualified by trellis coded quantization, after that the original signal was reconstructed by using 2D Orthogonal Matching Pursuit. The experimental results showed that the quantization method could effectively reduce the time and keep the quality of image compression.

关 键 词：3压缩感知 网格编码量化 2D正交匹配追踪算法 

分 类 号：TN919.81[电子电信—通信与信息系统]