{"title":"基于联合双边滤波的红外与可见光图像融合算法","authors":"Hua Cai, Guangqiu Chen, Zhi Liu, Z. Geng","doi":"10.1109/CISP-BMEI.2017.8302023","DOIUrl":null,"url":null,"abstract":"In view of the problem of the less correlative infrared(IFR) and visible(VI) images, a fusion methodology using joint bilateral filter (JBF) in the domain of non-subsampled contourlet transform (NSCT) is put forword. First, the images to be fused are divided into some sub-bands by NSCT. Then, the local window energy and the coefficient absolute value is regarded as the activity measure of approximate and detail sub-bands respectively. Decision maps are obtained by selecting max activity measure. Source images are regarded as the guided images and decision maps are used as input images in JBF. After filtering operation by JBF, the output images are treated as weight maps. The sub-band coefficients are fused by weighted average algorithm. Finally, the fused sub-bands are composed into a fused image by the inverse NSCT. The experiments on the IFR and VI image are carried out. For the assessment of fusion results, subjective and objective assessment methods are adopted. The results show that the proposed methodology can get better performance than some classical fusion method existed in the published literatures.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"4 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fusion algorithm of infrared and visible images based on joint bilateral filter\",\"authors\":\"Hua Cai, Guangqiu Chen, Zhi Liu, Z. Geng\",\"doi\":\"10.1109/CISP-BMEI.2017.8302023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In view of the problem of the less correlative infrared(IFR) and visible(VI) images, a fusion methodology using joint bilateral filter (JBF) in the domain of non-subsampled contourlet transform (NSCT) is put forword. First, the images to be fused are divided into some sub-bands by NSCT. Then, the local window energy and the coefficient absolute value is regarded as the activity measure of approximate and detail sub-bands respectively. Decision maps are obtained by selecting max activity measure. Source images are regarded as the guided images and decision maps are used as input images in JBF. After filtering operation by JBF, the output images are treated as weight maps. The sub-band coefficients are fused by weighted average algorithm. Finally, the fused sub-bands are composed into a fused image by the inverse NSCT. The experiments on the IFR and VI image are carried out. For the assessment of fusion results, subjective and objective assessment methods are adopted. The results show that the proposed methodology can get better performance than some classical fusion method existed in the published literatures.\",\"PeriodicalId\":6474,\"journal\":{\"name\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"volume\":\"4 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP-BMEI.2017.8302023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2017.8302023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fusion algorithm of infrared and visible images based on joint bilateral filter
In view of the problem of the less correlative infrared(IFR) and visible(VI) images, a fusion methodology using joint bilateral filter (JBF) in the domain of non-subsampled contourlet transform (NSCT) is put forword. First, the images to be fused are divided into some sub-bands by NSCT. Then, the local window energy and the coefficient absolute value is regarded as the activity measure of approximate and detail sub-bands respectively. Decision maps are obtained by selecting max activity measure. Source images are regarded as the guided images and decision maps are used as input images in JBF. After filtering operation by JBF, the output images are treated as weight maps. The sub-band coefficients are fused by weighted average algorithm. Finally, the fused sub-bands are composed into a fused image by the inverse NSCT. The experiments on the IFR and VI image are carried out. For the assessment of fusion results, subjective and objective assessment methods are adopted. The results show that the proposed methodology can get better performance than some classical fusion method existed in the published literatures.