{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:12:31Z","timestamp":1760231551707,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Foundation Strengthening Program","award":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"],"award-info":[{"award-number":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"]}]},{"name":"Basic Applied Technology of Heilongjiang Institutes Research Special Project","award":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"],"award-info":[{"award-number":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"],"award-info":[{"award-number":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005046","name":"Natural Science Foundation of Heilongjiang Province","doi-asserted-by":"publisher","award":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"],"award-info":[{"award-number":["2021-JCJQ-JJ-0026","ZNJZ2020WL01","51975170","LH2019F024"]}],"id":[{"id":"10.13039\/501100005046","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The gamma radiation environment is one of the harshest operating environments for image acquisition systems, and the captured images are heavily noisy. In this paper, we improve the multi-frame difference method for the characteristics of noise and add an edge detection algorithm to segment the noise region and extract the noise quantization information. A Gaussian mixture model of the gamma radiation noise is then established by performing a specific statistical analysis of the amplitude and quantity information of the noise. The established model is combined with the random walk algorithm to generate noise and achieve the prediction of image noise under different accumulated doses. Evaluated by objective similarity matching, there is no significant difference between the predicted image noise and the actual noise in subjective perception. The ratio of similarity-matched images in the sample from the predicted noise to the actual noise reaches 0.908. To further illustrate the spillover effect of this research, in the discussion session, we used the predicted image noise as the training set input to a deep residual network for denoising. The network model was able to achieve a good denoising effect. The results show that the prediction method proposed in this paper can accomplish the prediction of gamma radiation image noise, which is beneficial to the elimination of image noise in this environment.<\/jats:p>","DOI":"10.3390\/s22197325","type":"journal-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T03:30:37Z","timestamp":1664335837000},"page":"7325","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Gamma Radiation Image Noise Prediction Method Based on Statistical Analysis and Random Walk"],"prefix":"10.3390","volume":"22","author":[{"given":"Dongjie","family":"Li","sequence":"first","affiliation":[{"name":"Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration, Harbin University of Science and Technology, Harbin 150080, China"},{"name":"Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7635-7124","authenticated-orcid":false,"given":"Haipeng","family":"Deng","sequence":"additional","affiliation":[{"name":"Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration, Harbin University of Science and Technology, Harbin 150080, China"},{"name":"Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Yao","sequence":"additional","affiliation":[{"name":"Heilongjiang Institute of Atomic Energy, Harbin 150086, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jicheng","family":"Jiang","sequence":"additional","affiliation":[{"name":"Heilongjiang Institute of Atomic Energy, Harbin 150086, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yubao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Heilongjiang Institute of Atomic Energy, Harbin 150086, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"026301","DOI":"10.1088\/1361-6633\/80\/2\/026301","article-title":"Applications of Nuclear Physics","volume":"80","author":"Hayes","year":"2017","journal-title":"Rep. Prog. Phys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3546","DOI":"10.7498\/aps.55.3546","article-title":"A comparison of ionizing radiation damage in CMOS devices from Co-60 gamma rays, electrons and protons","volume":"55","author":"He","year":"2006","journal-title":"Acta Phys. Sin."},{"key":"ref_3","first-page":"1","article-title":"Comparison of the Dark Signal Degradation Induced by Gamma Ray, Proton, and Neutron Radiation in Pinned Photodiode CMOS Image Sensors","volume":"62","author":"Wang","year":"2019","journal-title":"Sci. China Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Watson, S., Duecker, D.A., and Groves, K. (2020). Localisation of Unmanned Underwater Vehicles (UUVs) in Complex and Confined Environments: A Review. Sensors, 20.","DOI":"10.3390\/s20216203"},{"key":"ref_5","first-page":"161","article-title":"Proton Radiation Damage in High-Resistivity n-Type Silicon CCDs","volume":"4669","author":"Bebek","year":"2002","journal-title":"Proceedings of the Sensors and Camera Systems for Scientific, Industrial, and Digital Photography Applications III"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2179","DOI":"10.1007\/s40747-021-00428-4","article-title":"Methods for Image Denoising Using Convolutional Neural Network: A Review","volume":"7","author":"Ilesanmi","year":"2021","journal-title":"Complex Intell. Syst."},{"key":"ref_7","first-page":"1678","article-title":"Radiation Image Denoising Based on Convolutional Neural Network","volume":"51","author":"Sun","year":"2017","journal-title":"At. Energy Sci. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Chen, J., Chao, H., and Yang, M. (2018, January 18\u201323). Image Blind Denoising with Generative Adversarial Network Based Noise Modeling. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake, UT, USA.","DOI":"10.1109\/CVPR.2018.00333"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1186\/s40537-019-0197-0","article-title":"A Survey on Image Data Augmentation for Deep Learning","volume":"6","author":"Shorten","year":"2019","journal-title":"J. Big Data"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"S47","DOI":"10.1097\/HP.0000000000000072","article-title":"Monitoring Performance of the Cameras under the High Dose-Rate Gamma Ray Environments","volume":"106","author":"Cho","year":"2014","journal-title":"Health Phys."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"102995","DOI":"10.1016\/j.jvcir.2020.102995","article-title":"Noise reduction for sonar images by statistical analysis and fields of experts","volume":"74","author":"Yuan","year":"2021","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1016\/j.crad.2016.11.021","article-title":"Radiation Dose-Reduction Strategies in Thoracic CT","volume":"72","author":"Moser","year":"2017","journal-title":"Clin. Radiol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1097\/HP.0b013e31824e71b6","article-title":"Dose Optimization for Different Medical Imaging Tasks from Exposure Index, Exposure Control Factor, and MAs in Digital Radiography","volume":"103","author":"Zhang","year":"2012","journal-title":"Health Phys."},{"key":"ref_14","unstructured":"Qin, Y., Deng, X., Guo, W., Zhao, Y., and Zhao, X. (2019). Noise model of low-dose CT projection data. China Conf., 129\u2013130."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1063\/1.1667257","article-title":"Performance of Uncooled Microcantilever Thermal Detectors","volume":"75","author":"Datskos","year":"2004","journal-title":"Rev. Sci. Instrum."},{"key":"ref_16","first-page":"180","article-title":"Improved three-frame difference moving target recognition algorithm","volume":"12","author":"Ding","year":"2022","journal-title":"Intell. Comput. Appl."},{"key":"ref_17","first-page":"630","article-title":"Moving Object Detection Algorithm Based on Improved Mixture Gaussian Model","volume":"25","author":"Xu","year":"2018","journal-title":"Control. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"e623","DOI":"10.7717\/peerj-cs.623","article-title":"The Coefficient of Determination R-Squared Is More Informative than SMAPE, MAE, MAPE, MSE and RMSE in Regression Analysis Evaluation","volume":"7","author":"Chicco","year":"2021","journal-title":"PeerJ Comput. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Li, J., Wu, Y., Zhang, Y., Zhao, J., and Si, Y. (2021). Parameter Estimation of Poisson\u2013Gaussian Signal-Dependent Noise from Single Image of CMOS\/CCD Image Sensor Using Local Binary Cyclic Jumping. Sensors, 21.","DOI":"10.3390\/s21248330"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s100970100031","article-title":"Gaussian Model Selection","volume":"3","author":"Massart","year":"2001","journal-title":"J. Eur. Math. Soc."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"182","DOI":"10.7498\/aps.71.20211838","article-title":"Single event transient effect of frontside and backside illumination image sensors under proton irradiation","volume":"71","author":"Fu","year":"2022","journal-title":"Acta Phys. Sin."},{"key":"ref_22","first-page":"565","article-title":"The Analysis of Mechanism on Ionization Radiation Damage Effects on CCD","volume":"29","author":"Wang","year":"2009","journal-title":"Nucl. Electron. Detect. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Reynolds, D.A. (2009). Gaussian Mixture Models. Encycl. Biom., 741.","DOI":"10.1007\/978-0-387-73003-5_196"},{"key":"ref_24","first-page":"102","article-title":"Research on Text Representation in Natural Language Processing","volume":"33","author":"Zhao","year":"2022","journal-title":"J. Softw."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L. ImageNet: A Large-Scale Hierarchical Image Database. Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition.","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref_26","first-page":"2261","article-title":"Review and Prospect of Full Reference Image Quality Assessment","volume":"49","author":"Gao","year":"2021","journal-title":"Acta Electron. Sin."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/19\/7325\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:40:22Z","timestamp":1760143222000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/19\/7325"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,27]]},"references-count":26,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["s22197325"],"URL":"https:\/\/doi.org\/10.3390\/s22197325","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,9,27]]}}}