{"title":"使用威布尔粒子滤波器的图像恢复","authors":"Ibrahim Sadok, M. Zribi","doi":"10.1109/PAIS56586.2022.9946893","DOIUrl":null,"url":null,"abstract":"Satellite images are frequently degraded throughout the data collection process. Degradation can involve blurring and different sources of noise. Image restoration attempts to reconstruct the original image from the corrupted data. In literature, different approaches depend on Kalman filtering exist for image restoration. However, it has certain limits in terms of stability, adaptability and visibility. In this article, a new technique based on the concept of particle filtering and the Weibull distribution (WPF) is proposed to restore images degraded by noise. Our approach is recursive and handles nonlinear situations. Simulation results are eventually exhibited a good performance of the WPF over conventional particle filters.","PeriodicalId":266229,"journal":{"name":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Restoration Using Weibull Particle Filters\",\"authors\":\"Ibrahim Sadok, M. Zribi\",\"doi\":\"10.1109/PAIS56586.2022.9946893\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Satellite images are frequently degraded throughout the data collection process. Degradation can involve blurring and different sources of noise. Image restoration attempts to reconstruct the original image from the corrupted data. In literature, different approaches depend on Kalman filtering exist for image restoration. However, it has certain limits in terms of stability, adaptability and visibility. In this article, a new technique based on the concept of particle filtering and the Weibull distribution (WPF) is proposed to restore images degraded by noise. Our approach is recursive and handles nonlinear situations. Simulation results are eventually exhibited a good performance of the WPF over conventional particle filters.\",\"PeriodicalId\":266229,\"journal\":{\"name\":\"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PAIS56586.2022.9946893\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PAIS56586.2022.9946893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Satellite images are frequently degraded throughout the data collection process. Degradation can involve blurring and different sources of noise. Image restoration attempts to reconstruct the original image from the corrupted data. In literature, different approaches depend on Kalman filtering exist for image restoration. However, it has certain limits in terms of stability, adaptability and visibility. In this article, a new technique based on the concept of particle filtering and the Weibull distribution (WPF) is proposed to restore images degraded by noise. Our approach is recursive and handles nonlinear situations. Simulation results are eventually exhibited a good performance of the WPF over conventional particle filters.