{"title":"基于IHS变换和ACE模型的多光谱和全色图像融合","authors":"Zijun Feng, Xiaoling Zhang, Jingbo Zhang","doi":"10.1109/ICCASE.2011.5997762","DOIUrl":null,"url":null,"abstract":"Image fusion involves merging two or more images into a single image with more information. Recently, many algorithms have been proposed for fusion of low-resolution multispectral (MS) and high-resolution panchromatic (Pan) images. In this paper, the intensity (I) component of fused image is obtained according to adaptively weighted combination to combine I component of MS image and Pan image in the Intensity-Hue-Saturation(IHS) space. Considering understanding of the human visual system, an automatic color equalization (ACE) algorithm is adopted for enhancing resulting image. Experimental results show that the proposed approach outperforms popular methods in improving spatial and spectral information.","PeriodicalId":369749,"journal":{"name":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fusion of Multispectral and Panchromatic Images Using IHS Transform and ACE Model\",\"authors\":\"Zijun Feng, Xiaoling Zhang, Jingbo Zhang\",\"doi\":\"10.1109/ICCASE.2011.5997762\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image fusion involves merging two or more images into a single image with more information. Recently, many algorithms have been proposed for fusion of low-resolution multispectral (MS) and high-resolution panchromatic (Pan) images. In this paper, the intensity (I) component of fused image is obtained according to adaptively weighted combination to combine I component of MS image and Pan image in the Intensity-Hue-Saturation(IHS) space. Considering understanding of the human visual system, an automatic color equalization (ACE) algorithm is adopted for enhancing resulting image. Experimental results show that the proposed approach outperforms popular methods in improving spatial and spectral information.\",\"PeriodicalId\":369749,\"journal\":{\"name\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCASE.2011.5997762\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCASE.2011.5997762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fusion of Multispectral and Panchromatic Images Using IHS Transform and ACE Model
Image fusion involves merging two or more images into a single image with more information. Recently, many algorithms have been proposed for fusion of low-resolution multispectral (MS) and high-resolution panchromatic (Pan) images. In this paper, the intensity (I) component of fused image is obtained according to adaptively weighted combination to combine I component of MS image and Pan image in the Intensity-Hue-Saturation(IHS) space. Considering understanding of the human visual system, an automatic color equalization (ACE) algorithm is adopted for enhancing resulting image. Experimental results show that the proposed approach outperforms popular methods in improving spatial and spectral information.