基于帧选择和极大似然估计的自适应光学图像多帧联合去卷积算法

Journal of Jilin University Science Edition

Previous Articles Next Articles

Multi-frame Joint Deconvolution Algorithm for Adaptive Optics ImagesBased on FrameSelection and Maximum Likelihood Estimation

ZHANG Lijuan^1,2, LI Dongming^2,3, YANG Jinhua², QIU Huan¹, LIU Ying⁴, LIU Huan³

1. College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China;2. School of OptoElectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China;3. School of Information Technology, Jilin Agricultural University, Changchun 130118, China; 4. School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun 130117, China

Received:2016-07-22 Online:2017-09-26 Published:2017-09-26
Contact: LI Dongming E-mail:ldmnuc@sina.com

Abstract

Abstract: In order to improve the spatial resolution of adaptive optics (AO) images, we proposed multi\|frame joint deconvolution algorithm for AO images based on frameselection and maximum likelihood estimation. The algorithm took maximum likelihood estimation as the basic principle. According to the Gaussian noise model of the image, the joint log likelihood function of multi\|frame AO images was established. Firstly, we selected frames of the observed multi\|AO
images and selected the high quality degraded images. Secondly, combined with the observed conditions and characteristics of AO system, the estimation model of point spread function was derived. Finally, we established iterative solution formulas, and obtained multi\|frame AO images joint deconvolution
method. The experimental results show that, compared with the RichardsonLucy EM or CPFAdaptive algorithm, the PSNR values of the proposed algorithm are increased by 9% and 5% respectively, and the Laplacian gradient moduli are increased by 11% and 8% respectively, and clearer target images are obtained.

Key words: frameselection technology, image restoration, point spread function (PSF), maximum likelihood estimation, adaptive optics (AO)

CLC Number:

TP751

ZHANG Lijuan, LI Dongming, YANG Jinhua, QIU Huan, LIU Ying, LIU Huan. Multi-frame Joint Deconvolution Algorithm for Adaptive Optics ImagesBased on FrameSelection and Maximum Likelihood Estimation[J].Journal of Jilin University Science Edition, 2017, 55(05): 1199-1206.

[1]	ZHANG Shizheng. Image Restoration Algorithm Based on Displacement Hermitian Splitting [J]. Journal of Jilin University Science Edition, 2019, 57(1): 97-104.
[2]	FENG Hailin, GUO Tian. Statistical Inference Based on Lifetime Data of Signatureand Doubly TypeⅡ Censored Systems [J]. Journal of Jilin University Science Edition, 2018, 56(5): 1125-1135.
[3]	ZHAO Bo, WANG Chunjie, LI Qun, TONG Zhizhen. Estimation and Application of Generalized Exponential Distribution of Scaling Parameter in Relati [J]. Journal of Jilin University Science Edition, 2018, 56(4): 864-870.
[4]	DU Yujing. Estimation of Parameters of Dynamic Reliability Model with Covariates [J]. Journal of Jilin University Science Edition, 2018, 56(2): 311-315.
[5]	TIAN Jiazhuo, WANG Dehui, LI Yanlin. Statistical Properties of (a,b) Class Distribution [J]. Journal of Jilin University Science Edition, 2016, 54(03): 480-486.
[6]	ZHANG Xuli, YANG Kai, WANG Dehui. Parameter Estimation for a Threshold Poisson LogLinear Autoregressive Model [J]. Journal of Jilin University Science Edition, 2016, 54(02): 251-256.
[7]	KE Xianbin, LIU Hongwei, YOU Hailong. Efficient Global Optimization Algorithm Based on Gradient Method [J]. Journal of Jilin University Science Edition, 2016, 54(01): 40-44.
[8]	ZHONG Lihong, HU Chengquan, JIN Jingji. Analysis and Implementation of Maximum LikelihoodEstimation Positioning Algorithm Based on RSSI [J]. Journal of Jilin University Science Edition, 2014, 52(03): 556-560.
[9]	SHI Sanzhi, YAN Li, WANG Zesheng. Maximum Likelihood Estimate of TimeVaryingParameter Autoregression Model [J]. Journal of Jilin University Science Edition, 2013, 51(06): 1098-1100.
[10]	ZHAO Zhiwen, M.S. Abdalroof, SHENG Dan shu. Using the maximum likelihood method, the authors studied parameter estimation and hypothesis on the equality of two Rayleigh distribution parameters under type Ⅰ censoring sample with missing data. We discussed the limiting properties of the estimator. Moreover, statistic on testing equality of the parameters from two Rayleigh distributions and its limit distribution were given. [J]. Journal of Jilin University Science Edition, 2013, 51(06): 1090-1094.
[11]	HAN Qi-Xing, SUN Wei-Zhi. Consistence and Asymptotic Distribution of Parameters Estimatorsof Food Limited Species Model with Random Perturbation [J]. J4, 2012, 50(03): 482-.
[12]	YIN Yun-Guang, CAO Yang, GUO Zhi-Chang, LI Jing. A Multiplicative Denoising Model of Color Images Based on Partial Differential Equations [J]. J4, 2011, 49(03): 424-429.
[13]	ZHAO Zhiwen,, WANG Siyang, WANG Rui ting, LI Ling. Parameter Estimation and Hypothesis Testing of Two ExponentialPopulations under Type Ⅰ Censoring Sample with Missed Data [J]. J4, 2009, 47(01): 26-30.
[14]	WU Danyang, ZHANG Zhongbo, MA Siliang. Palmprint Recognition Method Based on Ridgelet Transform [J]. J4, 2008, 46(05): 944-946.
[15]	WU Danyang, ZHANG Zhongbo, MA Siliang. An Image Restoration Method in the Contactless Palmprint Recognition [J]. J4, 2008, 46(02): 293-295.

Multi-frame Joint Deconvolution Algorithm for Adaptive Optics ImagesBased on FrameSelection and Maximum Likelihood Estimation

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 10