一种用于射电图像重建的改进RLTV算法

doi:10.3969/j.issn.1001-2400.2017.03.013

Abstract

Abstract:

This article simply introduces the basic theory of total variation and the Richardson-Lucy algorithm based on Total Variation. When this algorithm is applied to radio image reconstruction, accumulated discrepancy rises gradually during the iterations as the result of the approximation in derivation; hence the recovered images are often unsatisfactory. Aiming at this problem, this article comes up with a new Richardson-Lucy algorithm based on nonlinear projection and it is successfully applied to the heliograph image reconstruction. The simulation experiment shows that it turns out to be more effective to restore the image measured by using the improved Richardson-Lucy algorithm.

Key words: total variation, nonlinear projection, image reconstruction

WANG Shuzhen;XIE Kun;LI Li;ZHANG Jingang. Improved RLTV algorithm used to radio image reconstruction[J].Journal of Xidian University, 2017, 44(3): 72-76.

References

［1］ LEFKIMMIATIS S, UNSER M. Poisson Image Reconstruction with Hessian Schatten-norm Regularization［J］. IEEE Transactions on Image Processing, 2013, 22(11): 4314-4327.
［2］ WEN Y W, CHAN R H, ZENG T Y. Primal-dual Algorithms for Total Variation Based Image Restoration under Poisson Noise［J］. Science China Mathematics, 2016, 59(1): 141-160.
［3］ ZHANG X Q, FROMENT J. Total Variation Based Fourier Reconstruction and Regularization for Computer Tomography［C］//Proceedings of the IEEE Nuclear Science Symposium Conference: 4. Piscataway: IEEE, 2005: 2332-2336.
［4］匡涛, 黄力宇, 钟玉芳, 等. 不完全投影图像重建的压缩感知算法［J］. 西安电子科技大学学报, 2015, 42(4): 106-112.
KUANG Tao, HUANG Liyu, ZHONG Yufang, et al. An Improved Compressive Sensing Algorithm for CT Image Reconstruction with Incomplete Projection Data［J］. Journal of Xidian University, 2015, 42(4): 106-112.
［5］ NEEDELL D, WARD R. Stable Image Reconstruction Using Total Variation Minimization［J］. SIAM Journal of Imaging Sciences, 2013, 6(2): 1035-1058.
［6］ RICHARDSON W H. Bayesian-based Iterative Method of Image Restoration［J］. Journal of the Optical Society of America, 1972, 62(1): 55-59.
［7］ LUCY L B. An Iterative Technique for the Rectification of Observed Distributions［J］. The Astronomical Journal, 1974, 79(6): 745-754.
［8］ NICOLAS D, LAURE B F,CHRISTOPHE Z, et al. Richardson-Lucy Algorithm with Total Variation Regularization for 3D Confocal Microscope Deconvolution［J］. Microscopy Research and Technique, 2006, 69(4): 260-266.
［9］ NICOLAS D, LAURE B F,CHRISTOPHE Z, et al. 3D Microscopy Deconvolution Using Richardson-Lucy Algorithm with Total Variation Regularization［R］. Paris: INRIA, 2004.
［10］ XU L, REN J S J, LIU C, et al. Deep Convolutional Neural Network for Image Deconvolution［C］//Advances in Neural Information Processing Systems:2. Montral: Neural Information Processing Systems Foundation, 2014: 1790-1798.
［11］ HRADIS M, KOTERA J, ZEMCIK P, et al. Convolutional Neural Networks for Direct Text Deblurring［C］//Proceedings of the British Machine Vision Conference. Swansea: BMVA Press, 2015: 6.1-6.13.
［12］ SVOBODA P, HRADIS M, MARSIK L, et al. CNN for License Plate Motion Deblurring［C］//Proceedings of the International Conference on Image Processing. Piscataway: IEEE, 2016: 3832-3836.
［13］ RUDIN L I, OSHER S, FATEMI E. Nonlinear Total Variation Based Noise Removal Algorithms［J］. Physica D: Nonlinear Phenomena, 1992, 60(1/4): 259-268.
［14］ CHAMBOLLE A, CASELLES V, NOVAGA M, et al. An Introduction to Total Variation for Image Analysis［R］. Linz: Lecture Notes, 2010.

[1]	LI Kunlun,ZHANG Lu,XU Hongke,SONG Huansheng. Waveletdomain dilated network for fast low-dose CT image reconstruction [J]. Journal of Xidian University, 2020, 47(4): 86-93.
[2]	YANG Lei,YUE Yunze,LI Pucheng,ZHANG Tao,YANG Huan. Sparse representation of large dynamic range SAR imaging for multiple ground moving targets [J]. Journal of Xidian University, 2019, 46(5): 31-40.
[3]	HOU Yuqing;WEI Hongna;YI Huangjian;ZHANG Xu;HE Xiaowei. Imaging system of fluorescence molecular tomography with spiral excitation [J]. Journal of Xidian University, 2018, 45(2): 97-102.
[4]	HUO Leigang;FENG Xiangchu;WANG Xudong;HUO Chunlei. Higherorder singular value decomposition- and total variation- regularized multiplicative noise removal model [J]. Journal of Xidian University, 2016, 43(3): 78-84.
[5]	LIU Qiaohong;LI Bin;LIN Min. Non-convex hybrid total variation method for image blind restoration [J]. Journal of Xidian University, 2016, 43(2): 120-125.
[6]	WANG Yong;FENG Tangzhi;CHEN Chuchu;QIAO Qianqian;YANG Xiaoyu;WANG Guodong. Adaptive sparse representation and total variation constraint based image reconstruction [J]. J4, 2016, 43(1): 12-17+109.
[7]	KUANG Tao;HUANG Liyu;ZHONG Yufang;LI Chao. Improved compressive sensing algorithm for CT image reconstruction with incomplete projection data [J]. J4, 2015, 42(4): 95-99+113.
[8]	BAI Jian;FENG Xiangchu. Model based on the integro-differential equation for multiplicative noise removal [J]. J4, 2013, 40(3): 132-138.
[9]	BAI Jian;FENG Xiangchu. Image decomposition using the non-convex functional [J]. J4, 2013, 40(2): 67-71+137.
[10]	WANG Shuzhen;LI Li;ZOU Zijian;ZHANG Xiaoping. Research on the solar image reconstruction method based on compressive sensing [J]. J4, 2013, 40(1): 76-80.
[11]	XU Jianlou;FENG Xiangchu;HAO Yan. Second order total generalized variational inpainting model and its algorithm [J]. J4, 2012, 39(5): 18-23.
[12]	LU Cheng-wu1;2. Multiscale decomposition of image under (B_V,E) frame [J]. J4, 2009, 36(1): 171-176.
[13]	JIANG Ling-ling;YIN Hai-qing;FENG Xiang-chu. Image decomposition based on sparse representations and a projected regularization method [J]. J4, 2007, 34(5): 800-804.
[14]	LU Cheng-wu1;2;SONG Yi-mei1;SONG Guo-xiang1. Total variation energy functional with restrictions on the finite ridgelet domain [J]. J4, 2007, 34(4): 669-672.
[15]	LI Min;FENG Xiang-chu. A denoising model using the total variation and wavelet method [J]. J4, 2006, 33(6): 980-984.

Improved RLTV algorithm used to radio image reconstruction

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 10