Annisa Yuniar Hidayah, Abduh Riski, Ahmad Kamsyakawuni
{"title":"用CELLULAR AUTOMATA方法修复红外图像","authors":"Annisa Yuniar Hidayah, Abduh Riski, Ahmad Kamsyakawuni","doi":"10.19184/mims.v18i2.17249","DOIUrl":null,"url":null,"abstract":"Image enhancement is needed because not all images have good quality, such as noise, too low contrast or blurry image. These problems are commonly found in images generated from infrared cameras, therefore this study uses infrared imagery as an image to be corrected. The method that will be used to improve the image, namely Cellular Automata method. The edge detection using the Prewitt operator will be used as the initial state of Cellular Automata cells. The results obtained from this research is Cellular Automata method can improve the quality of infrared image well. Visually, the Cellular Automata method successfully improves image contrast and retains the infrared image detail so as not to reduce the value of information from the image. Calculated using the Linear Index of Fuzziness, the results of the Cellular Automata method are better only on some imagery only when compared to the Histogram Equalization mode. \nKeywords: Infrared Image, Image Enhancement, Cellular Automata","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PERBAIKAN CITRA INFRA MERAH DENGAN METODE CELLULAR AUTOMATA\",\"authors\":\"Annisa Yuniar Hidayah, Abduh Riski, Ahmad Kamsyakawuni\",\"doi\":\"10.19184/mims.v18i2.17249\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image enhancement is needed because not all images have good quality, such as noise, too low contrast or blurry image. These problems are commonly found in images generated from infrared cameras, therefore this study uses infrared imagery as an image to be corrected. The method that will be used to improve the image, namely Cellular Automata method. The edge detection using the Prewitt operator will be used as the initial state of Cellular Automata cells. The results obtained from this research is Cellular Automata method can improve the quality of infrared image well. Visually, the Cellular Automata method successfully improves image contrast and retains the infrared image detail so as not to reduce the value of information from the image. Calculated using the Linear Index of Fuzziness, the results of the Cellular Automata method are better only on some imagery only when compared to the Histogram Equalization mode. \\nKeywords: Infrared Image, Image Enhancement, Cellular Automata\",\"PeriodicalId\":264607,\"journal\":{\"name\":\"Majalah Ilmiah Matematika dan Statistika\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Majalah Ilmiah Matematika dan Statistika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.19184/mims.v18i2.17249\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Majalah Ilmiah Matematika dan Statistika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19184/mims.v18i2.17249","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PERBAIKAN CITRA INFRA MERAH DENGAN METODE CELLULAR AUTOMATA
Image enhancement is needed because not all images have good quality, such as noise, too low contrast or blurry image. These problems are commonly found in images generated from infrared cameras, therefore this study uses infrared imagery as an image to be corrected. The method that will be used to improve the image, namely Cellular Automata method. The edge detection using the Prewitt operator will be used as the initial state of Cellular Automata cells. The results obtained from this research is Cellular Automata method can improve the quality of infrared image well. Visually, the Cellular Automata method successfully improves image contrast and retains the infrared image detail so as not to reduce the value of information from the image. Calculated using the Linear Index of Fuzziness, the results of the Cellular Automata method are better only on some imagery only when compared to the Histogram Equalization mode.
Keywords: Infrared Image, Image Enhancement, Cellular Automata
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