{"title":"Image registration and mosaicing of noisy acoustic camera images","authors":"Kio Kim, N. Intrator, N. Neretti","doi":"10.1109/ICECS.2004.1399734","DOIUrl":null,"url":null,"abstract":"We introduce an algorithm for image registration and mosaicing on underwater sonar image sequences characterized by a high noise level, inhomogeneous illumination and low frame rate. For a planar surface viewed through a pinhole camera undergoing translational and rotational motion, registration can be obtained via a projective transformation. For an acoustic camera, we show that, under the same conditions, an affine transformation is a good approximation. We propose a novel image fusion, which maximizes the signal-to-noise ratio of the mosaic image. The full procedure includes illumination correction, feature based transformation estimation, and image fusion for mosaicing.","PeriodicalId":38467,"journal":{"name":"Giornale di Storia Costituzionale","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Giornale di Storia Costituzionale","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECS.2004.1399734","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Arts and Humanities","Score":null,"Total":0}
引用次数: 10
Abstract
We introduce an algorithm for image registration and mosaicing on underwater sonar image sequences characterized by a high noise level, inhomogeneous illumination and low frame rate. For a planar surface viewed through a pinhole camera undergoing translational and rotational motion, registration can be obtained via a projective transformation. For an acoustic camera, we show that, under the same conditions, an affine transformation is a good approximation. We propose a novel image fusion, which maximizes the signal-to-noise ratio of the mosaic image. The full procedure includes illumination correction, feature based transformation estimation, and image fusion for mosaicing.