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Intensity normalization of sidescan sonar imagery
Departamento de Eletrónica, Telecomunicações e Informática (DETI), Universidade de Aveiro, Aveiro, Portugal.
Departamento de Eletrónica, Telecomunicações e Informática (DETI), Universidade de Aveiro, Aveiro, Portugal.
Research Center on Software Technologies and Multimedia Systems for Sustainability (CITSEM), Universidad Politécnica de Madrid, Spain.
Research Center on Software Technologies and Multimedia Systems for Sustainability (CITSEM), Universidad Politécnica de Madrid, Spain.
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2016 (English)In: 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016, 2016, article id 7820967Conference paper, Published paper (Refereed)
Abstract [en]

Sonar imaging is currently the exemplary choice used in underwater imaging. However, since sound signals are absorbed by water, an image acquired by a sonar will have gradient illumination; thus, underwater maps will be difficult to process. In this work, we investigated this phenomenon with the objective to propose methods to normalize the images with regard to illumination. We propose to use MIxed exponential Regression Analysis (MIRA) estimated from each image that requires normalization. Two sidescan sonars have been used to capture the seabed in Lake Vattern in Sweden in two opposite directions west-east and east-west; hence, the task is extremely difficult due to differences in the acoustic shadows. Using the structural similarity index, we performed similarity analyses between corresponding regions extracted from the sonar images. Results showed that MIRA has superior normalization performance. This work has been carried out as part of the SWARMs project (http://www.swarms.eu/).

Place, publisher, year, edition, pages
2016. article id 7820967
Keywords [en]
acoustic shadow, dark channel prior, echo decay, exponential regression, illumination normalization, inverse square law, Sidscan sonar, Image analysis, Regression analysis, Sonar, Underwater acoustics, Underwater imaging, Dark channel priors, Image processing
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-34985DOI: 10.1109/IPTA.2016.7820967ISI: 000393589800019Scopus ID: 2-s2.0-85013223054ISBN: 9781467389105 (print)OAI: oai:DiVA.org:mdh-34985DiVA, id: diva2:1078700
Conference
6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016, 12 December 2016 through 15 December 2016
Available from: 2017-03-06 Created: 2017-03-06 Last updated: 2017-03-16Bibliographically approved

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Curuklu, Baran

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