[1]聂笃宪,陈一梅,陈鹤峰.去混合噪声的超分辨率图像重建算法[J].红外技术,2010,32(10):604-607.
 NIE Du-xian,CHEN Yi-mei,CHEN He-feng.Super-resolution Image Reconstruction Algorithm for mixed Noises Removal[J].Infrared Technology,2010,32(10):604-607.
点击复制

去混合噪声的超分辨率图像重建算法
分享到:

《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
32卷
期数:
2010年第10期
页码:
604-607
栏目:
出版日期:
2010-10-20

文章信息/Info

Title:
Super-resolution Image Reconstruction Algorithm for mixed Noises Removal
文章编号:
1001-8891(2010)10-0604-04
作者:
聂笃宪1陈一梅2陈鹤峰3
1.华南农业大学理学院,广东 广州 510642;2.仲恺农业工程学院图书馆,广东 广州 510225;
3.广东工业大学数学学院,广东 广州 510090

Author(s):
NIE Du-xian1CHEN Yi-mei2CHEN He-feng3
1.Department of Science, South China Agricultural University, Guangzhou Guangdong 510642, China;
2.Library, Zhongkai University of Agriculture and Technology, Guangzhou Guangdong 510225, China;
3.Department of Mathematics, Guangdong University of Technology, Guangzhou Guangdong 510090, China

关键词:
超分辨率去混合噪声全变分正则化两步方法图像重建
Keywords:
super-resolutionmixed noises removaltotal variationregularizationtwo-phase methodimage reconstruction
分类号:
TN919.8
文献标志码:
A
摘要:
研究了混合噪声即高斯白噪声加椒盐噪声所降质的超分辨率图像重建模型,提出了基于全变分正则化方法和两步方法的超分辨率图像重建方法,并应用Chambolle投影算法对模型进行求解;通过实验仿真,实验结果表明本文提出的方法比基于传统的全变分正则化方法无论是在运行速度,MSE与SNR评价指标上还是在视觉效果方面都具有明显的优越性。
Abstract:
Super-resolution image reconstruction models degraded by mixed Gaussian plus salt& pepper noises are studied in the paper. The method is proposed combing total variation regularization method and two-phase method. The proposed method is used to reconstruct super-resolution image, which was solved by employing Chambolle’s projection algorithm. Compared with the traditional super-resolution methods based on least mean square and total variation by using simulation experiments, the experimental results confirm the effectiveness of the proposed method and demonstrate its superiority from fidelity, processing time, MSE and SNR.

参考文献/References:

[1] ?Tsai R T, Huang T S.Multiframe image restoration and registration[J]. Advances in Computer Vision and Image Processing, 1984(1): 317-319.
[2] ?Elad M, Feuer A. Super resolution restoration of an image sequence:adaptive filtering approach[J]. IEEE Transactions on Image Processing, 1999, 8(3): 387-395..
[3] ?Patti A J, Sezan M I, Tekalp A M. Super resolution video reconstruction with arbitrary sampling lattices and nonzero aperture time[J]. IEEE Transactions on Image Processing, 1997, 6(8): 1064-1076.
[4] ?L. Bar, A. Brook, N. Schen, and N. Kiryati. Deblurring of color images corrupted by salt-and-pepper noise[J]. IEEE Trans. Image Process, 2007, 16: 1101-1111.
[5] ?L. Bar, N. Schen, N. Kiryati. Image deblurring in the presence of impulsive noise[J]. Int. J. Computer Vision, 2006, 70: 279-298.
[6] ?RH Chan, C.W. Ho, M. Nikolova. Salt-andpepper noise removal by median-type noise detectors and detail-preserving regularization[J]. IEEE Trans. Image Process, 2005, 14(10): 1479-1485.
[7] ? H. Eng, K. Ma, Noise adaptive soft-switching median filter[J]. IEEE Trans. Image Process, 2001, 10: 242-251
[8] ?G. Pok, J. Liu, A. Nair. Selective removal of impulse noise based on homogeneity level information[J]. IEEE Trans. Image Process, 2003, 12: 85-92
[9] ?J.F. Cai, R.H. Chan, and M. Nikolova. Two-Phase Methods for Deblurring Images Corrupted by Impulse Plus Gaussian Noise[J]. AIMS Journal on Inverse Problems and Imaging, 2008, 2(2): 187-204.
[10] ?A. Chambolle, An algorithm for total variation minimization and applications, J. Math. Imaging Vision. , Vol. 20 (2004), pp. 89–97
[11] ?Zomet A, Peleg S. Efficient super-resolution and applications to mosaics[C]//International Conference on Pattern Recognition, 2000: 3-8.

相似文献/References:

[1]樊超,孙宁宁,夏旭.基于序列图像的超分辨率重建[J].红外技术,2010,32(5):279.
 FAN Chao,SUN Ning-ning,XIA Xu.Super-resolution Reconstruction Based on Image Sequences[J].Infrared Technology,2010,32(10):279.
[2]陈博洋,陈桂林,孙胜利.亚像元技术在图像采集系统中的应用[J].红外技术,2007,29(4):226.
 CHEN Bo-Yang,CHEN Gui-Lin,SUN Sheng-Li.Application of Subpixel Technology for Image Collection System[J].Infrared Technology,2007,29(10):226.
[3]浦利,金伟其,刘玉树,等.基于小波双立方配比插值的图像插值放大算法研究[J].红外技术,2006,28(8):453.
 PU Li,JIN Wei-qi,LIU Yu-shu,et al.A Study of Wavelet Bi-cubic Ratio Interpolation Algorithm[J].Infrared Technology,2006,28(10):453.
[4]徐宏财,向健勇,潘皓.一种改进的POCS算法的超分辨率图像重建[J].红外技术,2005,27(6):477.
 XU Hong-cai,XIANG Jian-yong,PAN Hao.An Improved POCS Algorithm for Super-resolution Image Reconstruction[J].Infrared Technology,2005,27(10):477.
[5]姚 敏,周 勤.一种低匹配误差敏感度的红外图像超分辨率算法[J].红外技术,2016,38(10):864.[doi:10.11846/j.issn.1001_8891.201610010]
 YAO Min,ZHOU Qin.An Infrared Images Super-resolution Algorithm with Low Registration Error Sensitivity [J].Infrared Technology,2016,38(10):864.[doi:10.11846/j.issn.1001_8891.201610010]
[6]刘 哲,黄世奇,姜 杰.基于引导滤波和多尺度局部自相似单幅红外图像超分辨率方法[J].红外技术,2017,39(4):345.[doi:10.11846/j.issn.1001_8891.201704009]
 LIU Zhe,HUANG Shiqi,JIANG Jie.Single Image Super Resolution Method Based on Multi-scale Self-similarity and Non Local Means [J].Infrared Technology,2017,39(10):345.[doi:10.11846/j.issn.1001_8891.201704009]
[7]刘 哲,韩九强,黄世奇.基于多引导滤波器的单幅图像超分辨率技术[J].红外技术,2017,39(10):920.[doi:10.11846/j.issn.1001_8891.201710009]
 LIU Zhe,HAN jiuqiang,HUANG Shiqi.Single Image Super-Resolution Based on Multi-Guided Filtering[J].Infrared Technology,2017,39(10):920.[doi:10.11846/j.issn.1001_8891.201710009]
[8]姜杰,刘哲,吕林涛.局部线性嵌入的快速单幅图像超分辨率技术[J].红外技术,2018,40(1):039.[doi:10.11846/j.issn.1001_8891.201801008]
 JIANG Jie,LIU Zhe,LV Lintao.Fast Single-image Super Resolution Technique Based on Local Linear Embedding[J].Infrared Technology,2018,40(10):039.[doi:10.11846/j.issn.1001_8891.201801008]
[9]蔡坤琪.快速图像超分辨率方法研究[J].红外技术,2018,40(3):269.[doi:10.11846/j.issn.1001_8891.201803012]
 CAI Kunqi.A Study on Rapid Image Super-resolution[J].Infrared Technology,2018,40(10):269.[doi:10.11846/j.issn.1001_8891.201803012]
[10]刘哲,黄文准,乌伟.基于级联线性回归的快速单幅图像超分辨率技术[J].红外技术,2018,40(9):894.[doi:10.11846/j.issn.1001_8891.201809011]
 LIU Zhe,HUANG Wenzhun,WU Wei.Fast Single Image Super Resolution Based on Cascaded Linear Regression[J].Infrared Technology,2018,40(10):894.[doi:10.11846/j.issn.1001_8891.201809011]

备注/Memo

备注/Memo:
收稿日期:2010-08-16.
作者简介:聂笃宪(1974-),男,硕士,讲师,主要研究领域为图像处理。
基金项目:华南农业校长基金,编号:2009K203,2008K011;广东省自然科学基金,编号:9251064201000009;国家青年基金项目,编号:60702030;国家自然科学基金项目,编号:50775079。

更新日期/Last Update: 2014-04-11