{"title":"基于空间变化散焦模糊图的图像重定位","authors":"Ali Karaali, C. Jung","doi":"10.1109/ICIP.2016.7532848","DOIUrl":null,"url":null,"abstract":"This paper presents a new image retargeting method that explores blur information. Given the input image, we compute the blur map and estimate in-focus regions. For retargeting, we first try to crop image boundaries as much as possible (preserving in-focus regions). If cropping is not enough, we use seam carving exploring a novel blur-aware energy function that concentrates the seams in blurred regions of the image. Experimental results show that the proposed blur-aware retargeting scheme works better at preserving in-focus objects than other competitive retargeting algorithms.","PeriodicalId":6521,"journal":{"name":"2016 IEEE International Conference on Image Processing (ICIP)","volume":"84 1","pages":"2693-2697"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Image retargeting based on spatially varying defocus blur map\",\"authors\":\"Ali Karaali, C. Jung\",\"doi\":\"10.1109/ICIP.2016.7532848\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new image retargeting method that explores blur information. Given the input image, we compute the blur map and estimate in-focus regions. For retargeting, we first try to crop image boundaries as much as possible (preserving in-focus regions). If cropping is not enough, we use seam carving exploring a novel blur-aware energy function that concentrates the seams in blurred regions of the image. Experimental results show that the proposed blur-aware retargeting scheme works better at preserving in-focus objects than other competitive retargeting algorithms.\",\"PeriodicalId\":6521,\"journal\":{\"name\":\"2016 IEEE International Conference on Image Processing (ICIP)\",\"volume\":\"84 1\",\"pages\":\"2693-2697\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Image Processing (ICIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2016.7532848\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2016.7532848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image retargeting based on spatially varying defocus blur map
This paper presents a new image retargeting method that explores blur information. Given the input image, we compute the blur map and estimate in-focus regions. For retargeting, we first try to crop image boundaries as much as possible (preserving in-focus regions). If cropping is not enough, we use seam carving exploring a novel blur-aware energy function that concentrates the seams in blurred regions of the image. Experimental results show that the proposed blur-aware retargeting scheme works better at preserving in-focus objects than other competitive retargeting algorithms.