{"title":"一种新的自下而上的显著性检测方法","authors":"Xiaolong Ma, Xudong Xie, K. Lam, Yisheng Zhong","doi":"10.1109/ISCE.2013.6570272","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new method for saliency detection. Unlike other algorithms, our method considers nonsalient regions first, and extracts information in the wavelet transform domain only. Our method need not perform the inverse transform back to the image domain, which can greatly reduce the computational requirements. Experimental results show that our method can achieve excellent results when compared to the state-of-the-art methods.","PeriodicalId":442380,"journal":{"name":"2013 IEEE International Symposium on Consumer Electronics (ISCE)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new bottom-up method for saliency detection\",\"authors\":\"Xiaolong Ma, Xudong Xie, K. Lam, Yisheng Zhong\",\"doi\":\"10.1109/ISCE.2013.6570272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new method for saliency detection. Unlike other algorithms, our method considers nonsalient regions first, and extracts information in the wavelet transform domain only. Our method need not perform the inverse transform back to the image domain, which can greatly reduce the computational requirements. Experimental results show that our method can achieve excellent results when compared to the state-of-the-art methods.\",\"PeriodicalId\":442380,\"journal\":{\"name\":\"2013 IEEE International Symposium on Consumer Electronics (ISCE)\",\"volume\":\"282 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Symposium on Consumer Electronics (ISCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCE.2013.6570272\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Symposium on Consumer Electronics (ISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCE.2013.6570272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a new method for saliency detection. Unlike other algorithms, our method considers nonsalient regions first, and extracts information in the wavelet transform domain only. Our method need not perform the inverse transform back to the image domain, which can greatly reduce the computational requirements. Experimental results show that our method can achieve excellent results when compared to the state-of-the-art methods.
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