{"title":"图像处理中的高阶光谱","authors":"Salwa Lagdali, M. Rziza","doi":"10.1109/ATSIP.2017.8075553","DOIUrl":null,"url":null,"abstract":"Higher order spectra are very useful in problems where either non Gaussianity, noise and non linearities are important. These properties are proved to be present in natural images. This yield higher order spectra and especially the third order, namely the bispectrum, to be an interesting tool in image processing. This paper presents higher order spectra in signal processing and their extension and applications to image processing, where the images are proved to be non Gaussian and non linear.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Higher order spectra in image processing\",\"authors\":\"Salwa Lagdali, M. Rziza\",\"doi\":\"10.1109/ATSIP.2017.8075553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Higher order spectra are very useful in problems where either non Gaussianity, noise and non linearities are important. These properties are proved to be present in natural images. This yield higher order spectra and especially the third order, namely the bispectrum, to be an interesting tool in image processing. This paper presents higher order spectra in signal processing and their extension and applications to image processing, where the images are proved to be non Gaussian and non linear.\",\"PeriodicalId\":259951,\"journal\":{\"name\":\"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATSIP.2017.8075553\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATSIP.2017.8075553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Higher order spectra are very useful in problems where either non Gaussianity, noise and non linearities are important. These properties are proved to be present in natural images. This yield higher order spectra and especially the third order, namely the bispectrum, to be an interesting tool in image processing. This paper presents higher order spectra in signal processing and their extension and applications to image processing, where the images are proved to be non Gaussian and non linear.