{"title":"基于高阶统计量的依赖于信号的薄膜颗粒噪声去除与生成","authors":"J. C. K. Yan, D. Hatzinakos","doi":"10.1109/HOST.1997.613491","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new noise filtering scheme that is based on higher-order statistics (HOS) for photographic images corrupted by signal-dependent film grain noise. In addition, reliable estimation of the noise parameter using HOS is proposed. This parameter estimation technique can be used to generate film grain noise which has applications in motion picture and television productions. Simulation results show that the proposed filter perform better than existing methods which are based on second-order statistics.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Signal-dependent film grain noise removal and generation based on higher-order statistics\",\"authors\":\"J. C. K. Yan, D. Hatzinakos\",\"doi\":\"10.1109/HOST.1997.613491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new noise filtering scheme that is based on higher-order statistics (HOS) for photographic images corrupted by signal-dependent film grain noise. In addition, reliable estimation of the noise parameter using HOS is proposed. This parameter estimation technique can be used to generate film grain noise which has applications in motion picture and television productions. Simulation results show that the proposed filter perform better than existing methods which are based on second-order statistics.\",\"PeriodicalId\":305928,\"journal\":{\"name\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1997.613491\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Signal-dependent film grain noise removal and generation based on higher-order statistics
In this paper, we propose a new noise filtering scheme that is based on higher-order statistics (HOS) for photographic images corrupted by signal-dependent film grain noise. In addition, reliable estimation of the noise parameter using HOS is proposed. This parameter estimation technique can be used to generate film grain noise which has applications in motion picture and television productions. Simulation results show that the proposed filter perform better than existing methods which are based on second-order statistics.