{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:47:57Z","timestamp":1740149277227,"version":"3.37.3"},"reference-count":31,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,4,6]],"date-time":"2017-04-06T00:00:00Z","timestamp":1491436800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Science Foundation of China","award":["61402193,61401347"]},{"name":"National Spark Program of China","award":["2015GA66004"]},{"name":"the National University Students Innovation Training Project of China","award":["201610193048,20161019305"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"An adaptive optics (AO) system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.<\/jats:p>","DOI":"10.3390\/s17040785","type":"journal-article","created":{"date-parts":[[2017,4,6]],"date-time":"2017-04-06T13:57:30Z","timestamp":1491487050000},"page":"785","source":"Crossref","is-referenced-by-count":8,"title":["Robust Multi-Frame Adaptive Optics Image Restoration Algorithm Using Maximum Likelihood Estimation with Poisson Statistics"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5531-0618","authenticated-orcid":false,"given":"Dongming","family":"Li","sequence":"first","affiliation":[{"name":"School of Information Technology, Jilin Agricultural University, Changchun 130118, China"},{"name":"School of Opto-Electronic Engineering, Changchun University of Science and Technology, Changchun 130022, China"},{"name":"CSIRO Data61, PO Box 76, Epping, NSW 1710, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5943-1989","authenticated-orcid":false,"given":"Changming","family":"Sun","sequence":"additional","affiliation":[{"name":"CSIRO Data61, PO Box 76, Epping, NSW 1710, Australia"}]},{"given":"Jinhua","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Opto-Electronic Engineering, Changchun University of Science and Technology, Changchun 130022, China"}]},{"given":"Huan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Technology, Jilin Agricultural University, Changchun 130118, China"}]},{"given":"Jiaqi","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Information Technology, Jilin Agricultural University, Changchun 130118, China"}]},{"given":"Lijuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"CSIRO Data61, PO Box 76, Epping, NSW 1710, Australia"},{"name":"College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3625","DOI":"10.12733\/jics20102009","article-title":"Research on blind deconvolution algorithm of multiframe turbulence-degraded images","volume":"10","author":"Zhang","year":"2013","journal-title":"J. Inf. Comput. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"880","DOI":"10.3390\/s150100880","article-title":"Fast image restoration for spatially varying defocus blur of imaging sensor","volume":"15","author":"Cheong","year":"2015","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6108","DOI":"10.3390\/s8096108","article-title":"Spectral-based blind image restoration method for thin TOMBO imagers","volume":"8","author":"Boussaid","year":"2008","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Christou, J., Hege, E., Jefferies, S., and Keller, C. (1994, January 9). Application of multiframe iterative blind deconvolution for diverse astronomical imaging. Proceedings of SPIE 2200, Amplitude and Intensity Spatial Interferometry II, Kailua Kona, HI, USA.","DOI":"10.1117\/12.177275"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4614","DOI":"10.1364\/AO.37.004614","article-title":"Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra","volume":"37","author":"Conan","year":"1998","journal-title":"Appl. Opt."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1109\/78.655423","article-title":"A novel blind deconvolution scheme for image restoration using recursive filtering","volume":"46","author":"Kundur","year":"1998","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2238","DOI":"10.1117\/1.1497615","article-title":"Supersampling multiframe blind deconvolution resolution enhancement of adaptive optics compensated imagery of low earth orbit satellites","volume":"41","author":"Gerwe","year":"2002","journal-title":"Opt. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"A69","DOI":"10.1051\/0004-6361\/201219489","article-title":"Extended-object reconstruction in adaptive-optics imaging: the multiresolution approach","volume":"555","author":"Gladysz","year":"2013","journal-title":"Astron. Astrophys."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/TIP.2008.2007354","article-title":"Variational Bayesian blind deconvolution using a total variation prior","volume":"18","author":"Babacan","year":"2009","journal-title":"IEEE Trans. Image Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1109\/78.80894","article-title":"Maximum likelihood blur identification and image restoration using the EM algorithm","volume":"39","author":"Katsaggelos","year":"1991","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1016\/j.patrec.2006.01.009","article-title":"An adaptive algorithm for image restoration using combined penalty functions","volume":"27","author":"Zhu","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_12","first-page":"781607","article-title":"Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method","volume":"2014","author":"Zhang","year":"2014","journal-title":"Abstr. Appl. Anal."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1877","DOI":"10.1117\/1.602572","article-title":"Adaptive image restoration based on hierarchical neural networks","volume":"39","author":"Yap","year":"2000","journal-title":"Opt. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1264","DOI":"10.1088\/0004-637X\/690\/2\/1264","article-title":"Solar coronal structure and stray light in TRACE","volume":"690","author":"DeForest","year":"2008","journal-title":"Astrophys. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1088\/0004-637X\/765\/2\/144","article-title":"Point-spread functions for the extreme-ultraviolet channels of SDO\/AIA telescopes","volume":"765","author":"Poduval","year":"2013","journal-title":"Astrophys. J."},{"key":"ref_16","first-page":"492","article-title":"Non-parametric PSF estimation from celestial transit solar images using blind deconvolution","volume":"6","author":"Delouille","year":"2016","journal-title":"J. Space Weather Space Clim."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5029","DOI":"10.1016\/j.ijleo.2016.02.042","article-title":"Research on wavelet-based contourlet transform algorithm for adaptive optics image denoising","volume":"127","author":"Li","year":"2016","journal-title":"Opt. Int. J. Light Electron Opt."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.chinastron.2009.03.004","article-title":"Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution","volume":"33","author":"Tian","year":"2009","journal-title":"Chin. Astron. Astrophy."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Veran, J., Rigaut, F., Maitre, H., and Rouan, D. (1997, January 17). Estimation of the adaptive optics long-exposure point spread function using control loop data: recent developments. Proceedings of SPIE 3126, Adaptive Optics and Applications, San Diego, CA, USA.","DOI":"10.1117\/12.279066"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1051\/aas:1999253","article-title":"Effect of anisotropic imaging in off-axis adaptive astronomical systems","volume":"137","author":"Voitsekhovich","year":"1999","journal-title":"Astron. Astrophys. Suppl. Ser."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1051\/aas:2000145","article-title":"Characterization of adaptive optics point spread function for anisoplanatic imaging: Application to stellar field deconvolution","volume":"142","author":"Fusco","year":"2000","journal-title":"Astron. Astrophys. Suppl. Ser."},{"key":"ref_22","first-page":"003","article-title":"Predicted space varying point spread function model for anisoplanatic adaptive optics imaging","volume":"12","author":"Chang","year":"2011","journal-title":"Acta Opt. Sin."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"23227","DOI":"10.1364\/OE.19.023227","article-title":"Marginal blind deconvolution of adaptive optics retinal images","volume":"19","author":"Blanco","year":"2011","journal-title":"Opt. Express"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"065017","DOI":"10.1088\/0266-5611\/29\/6\/065017","article-title":"A convergent blind deconvolution method for post-adaptive optics astronomical imaging","volume":"29","author":"Prato","year":"2013","journal-title":"Inverse Prob."},{"key":"ref_25","first-page":"649","article-title":"Iterative multi-frame restoration algorithm of turbulence-degraded images based on Poisson model","volume":"25","author":"Hong","year":"2004","journal-title":"J. Astronaut. (Chin.)"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1364\/JOSAA.15.000978","article-title":"Iterative multiframe superresolution algorithms for atmospheric-turbulence-degraded imagery","volume":"15","author":"Sheppard","year":"1998","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3052","DOI":"10.1364\/OE.17.003052","article-title":"Restoration of turbulence-degraded extended object using the stochastic parallel gradient descent algorithm: Numerical simulation","volume":"17","author":"Yang","year":"2009","journal-title":"Opt. Express"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"B42","DOI":"10.1364\/JOSAA.24.000B42","article-title":"Blind image quality assessment through anisotropy","volume":"24","author":"Gabarda","year":"2007","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"313","DOI":"10.3788\/HPLPB20112302.0313","article-title":"Unsymmetrical multi-limit iterative blind deconvolution algorithm for adaptive optics image restoration","volume":"2","author":"Chen","year":"2011","journal-title":"High Power Laser Part. Beams (Chin.)"},{"key":"ref_30","unstructured":"(2016, November 03). Pixabay. Available online: https:\/\/pixabay.com\/en\/."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.mee.2013.03.113","article-title":"PSF calibration patterns selection based on sensitivity analysis","volume":"112","author":"Figueiro","year":"2013","journal-title":"Microelectron. Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/4\/785\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T22:51:16Z","timestamp":1736203876000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/4\/785"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,4,6]]},"references-count":31,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2017,4]]}},"alternative-id":["s17040785"],"URL":"https:\/\/doi.org\/10.3390\/s17040785","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2017,4,6]]}}}