Image denoising with adaptive sparse shrinkage method based on SURE estimation

Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (7): 195-198.

Previous Articles Next Articles

Image denoising with adaptive sparse shrinkage method based on SURE estimation

SHA Zhenghu1, YU Jian1, CUI Chen1，2

1.Department of Information Engineering, Electronic Engineering Institute of PLA, Hefei 230037, China
2.Key Laboratory of Electronic Restriction, Anhui Province, Hefei 230037, China

Online:2013-04-01 Published:2013-04-15

基于SURE无偏估计的图像自适应稀疏收缩去噪

沙正虎1，余剑1，崔琛1，2

1.解放军电子工程学院信息工程系，合肥 230037
2.安徽省电子制约技术重点实验室，合肥 230037

Abstract

Abstract: Under sparse representation framework, image denoising problems are investigated over over-complete dictionary and a novel adaptive threshold selection method is presented based on Stein unbiased risk estimator. Based on the one order derivable shrinkage function, the optimal objective function about threshold selection is derived and it is shown to be convex function on threshold, and then its global minimum is searched by golden section method. The choice of threshold is closer to the peak signal to PSNR-threshold curve’s maxima. Lena and Barbara are used in experimental simulation, and the results demonstrate the superior performance of the algorithm.

Key words: sparse representation, shrinkage denoising, general threshold, SURE estimation

摘要： 研究了基于过完备字典下稀疏表示框架的图像去噪问题，基于Stein无偏估计提出一种自适应阈值选择算法。在一阶可导收缩函数的基础上，推导了阈值选择的优化目标函数；证明该函数是关于阈值的凸函数，用黄金分割法搜索其全局最小值。该算法选择的阈值接近峰值信噪比-阈值曲线的极大值点。通过对Lena和Barbara图进行去噪实验，验证了算法的优越性。

关键词: 稀疏表示, 收缩去噪, 通用阈值, SURE无偏估计

SHA Zhenghu1, YU Jian1, CUI Chen1，2. Image denoising with adaptive sparse shrinkage method based on SURE estimation[J]. Computer Engineering and Applications, 2013, 49(7): 195-198.

沙正虎1，余剑1，崔琛1，2. 基于SURE无偏估计的图像自适应稀疏收缩去噪[J]. 计算机工程与应用, 2013, 49(7): 195-198.

[1]	ZHANG Xiaowen, REN Yongfeng. Image Matching Algorithm Combining Sparse Representation and Topological Similarity [J]. Computer Engineering and Applications, 2021, 57(8): 198-203.
[2]	TAO Tiwei, LIU Mingxia, WANG Mingliang, WANG Linlin, YANG Deyun, ZHANG Qiang. Effective Distance Based Low-Rank Representation [J]. Computer Engineering and Applications, 2021, 57(4): 141-147.
[3]	DING Yuxiang, BIAN Weixin, JIE Biao, ZHAO Jun. Super-Resolution Image Reconstruction Based on Neighborhood Regression and Sparse Representation [J]. Computer Engineering and Applications, 2021, 57(2): 230-236.
[4]	XU Ranran, WU Xiaojun, YIN Hefeng. Face Recognition via Discriminative Non-negative Representation Based Classification [J]. Computer Engineering and Applications, 2021, 57(13): 147-153.
[5]	WANG Yu, LIU Fan, WANG Fei. Autoencoder Based Sparse Representation for Single Sample Face Recognition [J]. Computer Engineering and Applications, 2021, 57(1): 168-172.
[6]	WANG Yusi, LU Deyang, LI Haiyang. Sparse Subspace Clustering Method Based on Fractional Function Constraints [J]. Computer Engineering and Applications, 2020, 56(7): 39-47.
[7]	LI Qiao, CHEN Huazhu, YANG Chunyu, LI Dan. Discriminative Analysis Dictionary and Classifier Learning for Pattern Classification [J]. Computer Engineering and Applications, 2020, 56(6): 165-171.
[8]	CAO Wenwen1, KANG Bin2, YAN Jun1, DING Wan1. Sparse Representation Target Tracking via Multi-Source Data Fusion [J]. Computer Engineering and Applications, 2019, 55(6): 1-7.
[9]	LIU Yuxin, HE Guanghui. Sparse Subspace Clustering with [k] Nearest Neighbor Constraint [J]. Computer Engineering and Applications, 2019, 55(3): 39-45.
[10]	ZHANG Kaibing, ZHENG Dongdong, JING Junfeng. Survey of Low-Resolution Face Recognition [J]. Computer Engineering and Applications, 2019, 55(22): 14-24.
[11]	HU Zhengping, LIU Huaibiao, SUN Degang. Kinship Verification Based on Neighborhood Repulsed Metric Sparse Discriminant for Single Sample [J]. Computer Engineering and Applications, 2019, 55(22): 133-139.
[12]	HU Zhengping, WANG Xin, SUN Degang. Visual Tracking Algorithm Based on Local Cosine Weight and Inverse Sparse Framework in Parameter Space [J]. Computer Engineering and Applications, 2019, 55(21): 206-213.
[13]	KONG Fanzhi, LI Jinlong, WU Dongmei. Target Tracking Algorithm Based on Low-Dimensional Feature and Online Weighted MIL [J]. Computer Engineering and Applications, 2019, 55(18): 116-121.
[14]	LIU Xia, LUO Wenhui, SU Yixin. Application of Improved Sparse Representation Algorithm in Face Recognition [J]. Computer Engineering and Applications, 2019, 55(14): 191-197.
[15]	WEI Jiamin1, FENG Jun1, BU Qirong1, GAO Yuan2, ZHAO Yan1. Off-line Chinese handwriting signature verification with hierarchical classification [J]. Computer Engineering and Applications, 2018, 54(8): 112-118.

Image denoising with adaptive sparse shrinkage method based on SURE estimation

基于SURE无偏估计的图像自适应稀疏收缩去噪

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics