{"title":"基于轮廓波和稀疏表示的红外图像与SAR图像融合改进方法","authors":"Xiuxia Ji","doi":"10.1109/IHMSC.2015.11","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an improved image fusion method of infrared image and SAR image based on the Contour let transform and sparse representation. For the method, it decompose the source image into the low frequency sub band coefficients and the high frequency sub band coefficients with the Contour let transform. The low frequency coefficients with lower sparseness are dealed with sparse representation, construct over complete dictionary, solve sparse coefficient over the trained dictionary, and choose the low frequency coefficients with the larger energy fusion rule. The high frequency sub band coefficients are fused by gradient maxim in. Different frequency coefficients are used to reconstruct the fused image by the inverse Contour let transform. Experimental results show that the proposed method is a feasible and effective image fusion method in term of visual quality and objective evaluation.","PeriodicalId":6592,"journal":{"name":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"7 1","pages":"282-285"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An Improved Image Fusion Method of Infrared Image and SAR Image Based on Contourlet and Sparse Representation\",\"authors\":\"Xiuxia Ji\",\"doi\":\"10.1109/IHMSC.2015.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an improved image fusion method of infrared image and SAR image based on the Contour let transform and sparse representation. For the method, it decompose the source image into the low frequency sub band coefficients and the high frequency sub band coefficients with the Contour let transform. The low frequency coefficients with lower sparseness are dealed with sparse representation, construct over complete dictionary, solve sparse coefficient over the trained dictionary, and choose the low frequency coefficients with the larger energy fusion rule. The high frequency sub band coefficients are fused by gradient maxim in. Different frequency coefficients are used to reconstruct the fused image by the inverse Contour let transform. Experimental results show that the proposed method is a feasible and effective image fusion method in term of visual quality and objective evaluation.\",\"PeriodicalId\":6592,\"journal\":{\"name\":\"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"volume\":\"7 1\",\"pages\":\"282-285\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC.2015.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2015.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Image Fusion Method of Infrared Image and SAR Image Based on Contourlet and Sparse Representation
In this paper, we propose an improved image fusion method of infrared image and SAR image based on the Contour let transform and sparse representation. For the method, it decompose the source image into the low frequency sub band coefficients and the high frequency sub band coefficients with the Contour let transform. The low frequency coefficients with lower sparseness are dealed with sparse representation, construct over complete dictionary, solve sparse coefficient over the trained dictionary, and choose the low frequency coefficients with the larger energy fusion rule. The high frequency sub band coefficients are fused by gradient maxim in. Different frequency coefficients are used to reconstruct the fused image by the inverse Contour let transform. Experimental results show that the proposed method is a feasible and effective image fusion method in term of visual quality and objective evaluation.