Kuldeep Purohit, Subeesh Vasu, A. Rajagopalan, V. Jyothi, Ramesh Raju
{"title":"拼接深水图像","authors":"Kuldeep Purohit, Subeesh Vasu, A. Rajagopalan, V. Jyothi, Ramesh Raju","doi":"10.1145/3009977.3010029","DOIUrl":null,"url":null,"abstract":"Numerous sources of distortions render mosaicing of underwater (UW) images an immensely challenging effort. Methods that can process conventional photographs (terrestrial/aerial) fail to deliver the desired results on UW images. Taking the sources of underwater degradations into account is central to ensuring quality performance. The work described in this paper specifically deals with the problem of mosaicing deep UW images captured by Remotely Operated Vehicles (ROVs). These images are mainly degraded by haze, color changes, and non-uniform illumination. We propose a framework that restores these images in accordance with a suitably derived degradation model. Furthermore, our scheme harnesses the scene geometry information present in each image to aid in constructing a mosaic that is free from artifacts such as local blurring, ghosting, double contouring and visible seams. Several experiments on real underwater images sequences have been carried out to demonstrate the performance of our mosaicing pipeline along with comparisons.","PeriodicalId":93806,"journal":{"name":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","volume":"33 1","pages":"74:1-74:8"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mosaicing deep underwater imagery\",\"authors\":\"Kuldeep Purohit, Subeesh Vasu, A. Rajagopalan, V. Jyothi, Ramesh Raju\",\"doi\":\"10.1145/3009977.3010029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Numerous sources of distortions render mosaicing of underwater (UW) images an immensely challenging effort. Methods that can process conventional photographs (terrestrial/aerial) fail to deliver the desired results on UW images. Taking the sources of underwater degradations into account is central to ensuring quality performance. The work described in this paper specifically deals with the problem of mosaicing deep UW images captured by Remotely Operated Vehicles (ROVs). These images are mainly degraded by haze, color changes, and non-uniform illumination. We propose a framework that restores these images in accordance with a suitably derived degradation model. Furthermore, our scheme harnesses the scene geometry information present in each image to aid in constructing a mosaic that is free from artifacts such as local blurring, ghosting, double contouring and visible seams. Several experiments on real underwater images sequences have been carried out to demonstrate the performance of our mosaicing pipeline along with comparisons.\",\"PeriodicalId\":93806,\"journal\":{\"name\":\"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing\",\"volume\":\"33 1\",\"pages\":\"74:1-74:8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3009977.3010029\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3009977.3010029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Numerous sources of distortions render mosaicing of underwater (UW) images an immensely challenging effort. Methods that can process conventional photographs (terrestrial/aerial) fail to deliver the desired results on UW images. Taking the sources of underwater degradations into account is central to ensuring quality performance. The work described in this paper specifically deals with the problem of mosaicing deep UW images captured by Remotely Operated Vehicles (ROVs). These images are mainly degraded by haze, color changes, and non-uniform illumination. We propose a framework that restores these images in accordance with a suitably derived degradation model. Furthermore, our scheme harnesses the scene geometry information present in each image to aid in constructing a mosaic that is free from artifacts such as local blurring, ghosting, double contouring and visible seams. Several experiments on real underwater images sequences have been carried out to demonstrate the performance of our mosaicing pipeline along with comparisons.