{"title":"多分辨率多传感器融合中的图像增强","authors":"J. Jang, Yong Sun Kim, J. Ra","doi":"10.1109/AVSS.2007.4425325","DOIUrl":null,"url":null,"abstract":"In multi-sensor image fusion, multi-resolution approaches became popular because they can preserve detailed information well. Among them, the gradient-based multi-resolution (GBMR) algorithm is known to effectively reduce ringing artifacts near edges compared with the discrete wavelet transform (DWT)-based algorithm. However, since the GBMR algorithm does not consider the diagonal direction, the ringing artifacts reduction is not satisfactory at diagonal edges. In this paper, we generalize the GBMR algorithm by adopting the wavelet structure. Thereby, the proposed algorithm improves the fusion process in high-frequency sub-bands so as to preserve details of input images. Meanwhile, the algorithm fuses the low-frequency sub-band by considering the overall contrast in the output image. To evaluate the proposed algorithm, we compare it with the DWT-based and GBMR algorithms. Experimental results clearly demonstrate that the proposed algorithm effectively reduces ringing artifacts for edges of all directions and greatly enhances the overall contrast while minimizing visual information loss.","PeriodicalId":371050,"journal":{"name":"2007 IEEE Conference on Advanced Video and Signal Based Surveillance","volume":"192 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Image enhancement in multi-resolution multi-sensor fusion\",\"authors\":\"J. Jang, Yong Sun Kim, J. Ra\",\"doi\":\"10.1109/AVSS.2007.4425325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In multi-sensor image fusion, multi-resolution approaches became popular because they can preserve detailed information well. Among them, the gradient-based multi-resolution (GBMR) algorithm is known to effectively reduce ringing artifacts near edges compared with the discrete wavelet transform (DWT)-based algorithm. However, since the GBMR algorithm does not consider the diagonal direction, the ringing artifacts reduction is not satisfactory at diagonal edges. In this paper, we generalize the GBMR algorithm by adopting the wavelet structure. Thereby, the proposed algorithm improves the fusion process in high-frequency sub-bands so as to preserve details of input images. Meanwhile, the algorithm fuses the low-frequency sub-band by considering the overall contrast in the output image. To evaluate the proposed algorithm, we compare it with the DWT-based and GBMR algorithms. Experimental results clearly demonstrate that the proposed algorithm effectively reduces ringing artifacts for edges of all directions and greatly enhances the overall contrast while minimizing visual information loss.\",\"PeriodicalId\":371050,\"journal\":{\"name\":\"2007 IEEE Conference on Advanced Video and Signal Based Surveillance\",\"volume\":\"192 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Conference on Advanced Video and Signal Based Surveillance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AVSS.2007.4425325\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Conference on Advanced Video and Signal Based Surveillance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AVSS.2007.4425325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image enhancement in multi-resolution multi-sensor fusion
In multi-sensor image fusion, multi-resolution approaches became popular because they can preserve detailed information well. Among them, the gradient-based multi-resolution (GBMR) algorithm is known to effectively reduce ringing artifacts near edges compared with the discrete wavelet transform (DWT)-based algorithm. However, since the GBMR algorithm does not consider the diagonal direction, the ringing artifacts reduction is not satisfactory at diagonal edges. In this paper, we generalize the GBMR algorithm by adopting the wavelet structure. Thereby, the proposed algorithm improves the fusion process in high-frequency sub-bands so as to preserve details of input images. Meanwhile, the algorithm fuses the low-frequency sub-band by considering the overall contrast in the output image. To evaluate the proposed algorithm, we compare it with the DWT-based and GBMR algorithms. Experimental results clearly demonstrate that the proposed algorithm effectively reduces ringing artifacts for edges of all directions and greatly enhances the overall contrast while minimizing visual information loss.