{"title":"小波分析与色彩空间分解在人体荧光标记图像组织研究中的应用","authors":"Vyacheslav Lyashenko, O. Kobylin, A. Shafronenko","doi":"10.1109/CAOL46282.2019.9019575","DOIUrl":null,"url":null,"abstract":"The image of human fluorescently labeled tissues is taken as short view of the subject. These images are in RGB format. We must highlight areas of interest. In this case we use the ideology of wavelets. It allows us to find a lot of points of the brightness change in the original image. We get additional information, as well as decompose the input image into separate color spaces. This allows us to specify the areas of interest for the original image. The advantage of the original image decomposition into separate color spaces is clearly shown in comparison with the image in the RGB format. The results are received by using the real images.","PeriodicalId":308704,"journal":{"name":"2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wavelet Analysis and Decomposition Into Color Spaces in Researching of Human Fluorescently Labeled Images Tissues\",\"authors\":\"Vyacheslav Lyashenko, O. Kobylin, A. Shafronenko\",\"doi\":\"10.1109/CAOL46282.2019.9019575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The image of human fluorescently labeled tissues is taken as short view of the subject. These images are in RGB format. We must highlight areas of interest. In this case we use the ideology of wavelets. It allows us to find a lot of points of the brightness change in the original image. We get additional information, as well as decompose the input image into separate color spaces. This allows us to specify the areas of interest for the original image. The advantage of the original image decomposition into separate color spaces is clearly shown in comparison with the image in the RGB format. The results are received by using the real images.\",\"PeriodicalId\":308704,\"journal\":{\"name\":\"2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAOL46282.2019.9019575\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAOL46282.2019.9019575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wavelet Analysis and Decomposition Into Color Spaces in Researching of Human Fluorescently Labeled Images Tissues
The image of human fluorescently labeled tissues is taken as short view of the subject. These images are in RGB format. We must highlight areas of interest. In this case we use the ideology of wavelets. It allows us to find a lot of points of the brightness change in the original image. We get additional information, as well as decompose the input image into separate color spaces. This allows us to specify the areas of interest for the original image. The advantage of the original image decomposition into separate color spaces is clearly shown in comparison with the image in the RGB format. The results are received by using the real images.