[1]周飞飞,李雷.小波高频子带变换裁剪阈值SAMP算法研究[J].计算机技术与发展,2014,24(05):83-86.
　ZHOU Fei-fei,LI Lei.Research on Clipping Threshold SAMP Algorithm Based on High Frequency Sub-band Wavelet Transform[J].,2014,24(05):83-86.
点击复制

小波高频子带变换裁剪阈值SAMP算法研究()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年05期
页码:
83-86
栏目:
智能、算法、系统工程
出版日期:
2014-05-31

文章信息/Info

Title:
Research on Clipping Threshold SAMP Algorithm Based on High Frequency Sub-band Wavelet Transform
文章编号:
1673-629X（2014）05-0083-04
作者:
周飞飞; 李雷
南京邮电大学 理学院
Author(s):
ZHOU Fei-fei; LI Lei
关键词:
压缩感知; 图像重构; 高频子带小波变换; 裁剪阈值SAMP算法
Keywords:
compressed sensing; image reconstruction; high frequency sub-band wavelet transform; cropping threshold sparse adaptive matching pursuit
分类号:
TP301.6
文献标志码:
A
摘要:
文中首先针对离散小波变换( DWT)破坏了低频逼近系数之间的相关性，导致重构质量变差的问题，提出小波高频子带变换( HFSBWT)的稀疏表示方法。其次针对稀疏度自适应匹配追踪( SAMP)算法的原子候选集在每次迭代时成倍增加造成存储空间浪费和重构时间变长等问题，提出裁剪阈值稀疏度自适应匹配追踪( CTSAMP)算法。最后仿真结果表明：对于同一重构算法，小波高频子带变换的图像重构峰值信噪比提高3 dB左右。在小波高频子带变换稀疏表示后采用裁剪阈值稀疏度自适应匹配追踪算法，重构图像的性能有了明显的提高，重构时间缩短一半。
Abstract:
Firstly,aiming at the problem which the Discrete Wavelet Transform ( DWT) destroyed the correlation between low-frequency approximation coefficients,resulting in the bad quality of reconstruction,put forward a new way of sparse representation named High Fre-quency Sub-Band Wavelet Transform ( HFSBWT) . Secondly,in view of the problem that Sparsity Adaptive Matching Pursuit ( SAMP) algorithm atoms candidate set multiplied lead to wasting storage space and lengthening reconstruction time at each iteration,propose a method named Clipping Threshold Sparsity Adaptive Matching Pursuit ( CTSAMP) algorithms. The simulation results show that for the same reconstruction algorithm,the image reconstruction PSNR of HFSBWT increases about 3 dB. For image signal sparse representation use HFSBWT after CTSAMP reconstruction algorithm,the reconstructed performance of image has been significantly improved,and re-construction time has cut in half.

相似文献/References:

[1]张爱华 薄禄裕 盛飞 杨培.基于小波变换的压缩感知在图像加密中的应用[J].计算机技术与发展,2011,(12):145.
　ZHANG Ai-hua,BO Lu-yu,SHENG Fei,et al.Compressed Sensing Based on Single Layer Wavelet Transform for Image Encryption[J].,2011,(05):145.
[2]王韦刚 庄伟胤.基于NIOS Ⅱ的图像压缩感知[J].计算机技术与发展,2012,(04):12.
　WANG Wei-gang,ZHUANG Wei-yin.Compressed Sensing of Image Based on NIOS Ⅱ[J].,2012,(05):12.
[3]王韦刚 胡海峰.基于压缩感知的协作频谱检测[J].计算机技术与发展,2012,(12):241.
　WANG Wei-gang,HU Hai-feng.Collaborative Spectrum Detection Based on Compressed Sensing[J].,2012,(05):241.
[4]张晓咏,熊承义,胡开云,等.基于灰度纹理信息的图像压缩感知编码与重构[J].计算机技术与发展,2013,(01):47.
[5]刘洋,季薇,侯晓赟.一种改进的基于 OMP 重建的宽带频谱感知算法[J].计算机技术与发展,2013,(01):99.
　LIU Yang,JI Wei,HOU Xiao-yun.A Modified Spectrum Sensing Algorithm for Wideband Cognitive Radio Based on OMP[J].,2013,(05):99.
[6]彭钰,侯晓赟.基于二维压缩感知的双选信道估计[J].计算机技术与发展,2013,(10):220.
　PENG Yu,HOU Xiao-yun.Doubly Selective Channel Estimation Based on Two Dimension Compressed Sensing[J].,2013,(05):220.
[7]李熔.基于截尾估计的概率估计方法[J].计算机技术与发展,2014,24(02):101.
　LI Rong.Probability Estimation Method Based on Truncated Estimation[J].,2014,24(05):101.
[8]李燕,王博.基于压缩感知的数据压缩与检测[J].计算机技术与发展,2014,24(03):198.
　LI Yan,WANG Bo.Data Compression and Detection Based on Compressive Sensing[J].,2014,24(05):198.
[9]刘正其,季薇.一种改进的基于BOMP的宽带频谱感知算法[J].计算机技术与发展,2014,24(06):118.
　LIU Zheng-qi,JI Wei.A Modified Spectrum Sensing Algorithm for Wideband Cognitive Radio Based on BOMP[J].,2014,24(05):118.
[10]徐志坚,邱晓晖. 采用压缩感知的协作多点信道反馈算法研究[J].计算机技术与发展,2014,24(10):221.
　XU Zhi-jian,QIU Xiao-hui. Study on Channel Feedback Algorithm Using Compressed Sensing for Coordinated Multiple Point[J].,2014,24(05):221.
[11]石曼曼,李雷.基于分段可调节OMP算法的图像压缩感知算法[J].计算机技术与发展,2016,26(11):14.
　SHI Man-man,LI Lei. An Image Compressed Sensing Algorithm Based on Novel Stagewise Regulation OMP Algorithm[J].,2016,26(05):14.
[12]刘艳,宋欢欢,李雷. 压缩感知中基于快速不动点迭代算法的研究[J].计算机技术与发展,2017,27(03):52.
　LIU Yan,SONG Huan-huan,LI Lei. Research on Iteration Algorithm Based on a Fast Fixed Point in Compressed Sensing[J].,2017,27(05):52.
[13]石曼曼,李 雷.一种改进的 OMP 算法及其在图像重构上的应用[J].计算机技术与发展,2018,28(02):94.[doi:10．3969/j．issn．1673－629X．2018．02．021]
　SHI Manman,LI Lei.An Improved Orthogonal Matching Pursuit Algorithm and Its Application in Image Ｒeconstruction[J].,2018,28(05):94.[doi:10．3969/j．issn．1673－629X．2018．02．021]

更新日期/Last Update: 1900-01-01