Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2488
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dc.contributor.authorMallik, S-
dc.contributor.authorKhan, S S-
dc.contributor.authorPati, U C-
dc.date.accessioned2016-04-13T12:49:25Z-
dc.date.available2016-04-13T12:49:25Z-
dc.date.issued2016-03-
dc.identifier.citationIEEE International Conference on Innovations in information, Embedded and Communication Systems (ICIIECS16), Coimbatore, Tamilnadu, India, 17-18 March 2016en_US
dc.identifier.urihttp://hdl.handle.net/2080/2488-
dc.descriptionCopyright belongs to proceeding publisheren_US
dc.description.abstractThe human incapability in diving in the deep ocean for a long time has increased the challenges of underwater analysis. However, the challenges contain problems like aggressive light absorption and disrupting scattering effect in the deep ocean enabling lighting problem. These days UROV (Underwater remotely operated vehicle) are used to acquire images in deep ocean which contains additional artificial lighting still unable to provide good and clear images. In this paper, we have focused on the underwater image enhancements techniques mainly required for sea floor exploration and navigation, underwater environment monitoring, finding possibilities for applied purposes for civil engineering and assessment of coral reefs [1]. A method which contains a haze removal algorithm followed by a Contrast Limited Adaptive Histogram Equalization (CLAHE) color model has been introduced. So mainly, we concentrate on the underwater image enhancement through haze removal algorithm by dark channel prior technique. But, it has tendency to darken the image in some situation but shows a good result by reducing haze and noise effect. In order to improve the dehazing result, a histogram equalization technique has been taken. CLAHE on RGB model has been followed in our approach to change the level of contrast and intensity of dehaze image. In the end, a color correction algorithm for visually appreciable result has been used. Our experimental results show that the proposed algorithm has significantly improved quality of underwater images visually as well as quantifiably by enhancing the contrast of the image and reducing noise as well as artifacts in the imageen_US
dc.publisherIEEEen_US
dc.subjectHaze removalen_US
dc.subjectDark channel prioren_US
dc.subjectCLAHERGBen_US
dc.subjectImage Enhancementen_US
dc.titleUnderwater Image Enhancement Based on Dark Channel Prior and Histogram Equalizationen_US
dc.typeArticleen_US
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