{"title":"使用多模态增强技术对浓雾和朦胧天气图像的视觉改进","authors":"P. K. Chaturvedi, R. Vijay, R. Nirala","doi":"10.1109/ICMETE.2016.68","DOIUrl":null,"url":null,"abstract":"Image enhancement processes consist of a collection of techniques that inquire about to improve the visual appearance of degraded image. This paper introduces a multimodal enhancement technique for dense foggy images. The present available techniques don't work in low visibility like dense fog. The proposed methods changes the intensity component among the converted HIS components from the RGB components of the original foggy image. Again by converting back to RGB components, the foggy image tends to appear more clearly than the original image in terms of Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).[2] Finally the enhanced foggy image is obtained and the results are presented [9].","PeriodicalId":167368,"journal":{"name":"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Visual Improvement for Dense Foggy & Hazy Weather Images, Using Multimodal Enhancement Techniques\",\"authors\":\"P. K. Chaturvedi, R. Vijay, R. Nirala\",\"doi\":\"10.1109/ICMETE.2016.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image enhancement processes consist of a collection of techniques that inquire about to improve the visual appearance of degraded image. This paper introduces a multimodal enhancement technique for dense foggy images. The present available techniques don't work in low visibility like dense fog. The proposed methods changes the intensity component among the converted HIS components from the RGB components of the original foggy image. Again by converting back to RGB components, the foggy image tends to appear more clearly than the original image in terms of Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).[2] Finally the enhanced foggy image is obtained and the results are presented [9].\",\"PeriodicalId\":167368,\"journal\":{\"name\":\"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMETE.2016.68\",\"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 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMETE.2016.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visual Improvement for Dense Foggy & Hazy Weather Images, Using Multimodal Enhancement Techniques
Image enhancement processes consist of a collection of techniques that inquire about to improve the visual appearance of degraded image. This paper introduces a multimodal enhancement technique for dense foggy images. The present available techniques don't work in low visibility like dense fog. The proposed methods changes the intensity component among the converted HIS components from the RGB components of the original foggy image. Again by converting back to RGB components, the foggy image tends to appear more clearly than the original image in terms of Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).[2] Finally the enhanced foggy image is obtained and the results are presented [9].