{"title":"SAR和无人机图像纹理测度容量的梯度分布矩阵和空隙性","authors":"A. Potapov, F. F. Lazko","doi":"10.1109/RADAR.2016.8059256","DOIUrl":null,"url":null,"abstract":"This article gives a brief description of two widely used texture measures of SAR and UAVs images. They are gradients distribution or co-occurrence matrices and lacunarity. We also provide detailed outlines of mentioned above matrices calculation in order to introduce the way of texture features extraction. At the end of the article, we examine functional connection between the first texture feature and absolute value of offset.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Gradients distribution matrices and lacunarity in the capacity of texture measures of SAR and UAVs images\",\"authors\":\"A. Potapov, F. F. Lazko\",\"doi\":\"10.1109/RADAR.2016.8059256\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article gives a brief description of two widely used texture measures of SAR and UAVs images. They are gradients distribution or co-occurrence matrices and lacunarity. We also provide detailed outlines of mentioned above matrices calculation in order to introduce the way of texture features extraction. At the end of the article, we examine functional connection between the first texture feature and absolute value of offset.\",\"PeriodicalId\":245387,\"journal\":{\"name\":\"2016 CIE International Conference on Radar (RADAR)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 CIE International Conference on Radar (RADAR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2016.8059256\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 CIE International Conference on Radar (RADAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2016.8059256","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gradients distribution matrices and lacunarity in the capacity of texture measures of SAR and UAVs images
This article gives a brief description of two widely used texture measures of SAR and UAVs images. They are gradients distribution or co-occurrence matrices and lacunarity. We also provide detailed outlines of mentioned above matrices calculation in order to introduce the way of texture features extraction. At the end of the article, we examine functional connection between the first texture feature and absolute value of offset.