Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/2488
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mallik, S | - |
dc.contributor.author | Khan, S S | - |
dc.contributor.author | Pati, U C | - |
dc.date.accessioned | 2016-04-13T12:49:25Z | - |
dc.date.available | 2016-04-13T12:49:25Z | - |
dc.date.issued | 2016-03 | - |
dc.identifier.citation | IEEE International Conference on Innovations in information, Embedded and Communication Systems (ICIIECS16), Coimbatore, Tamilnadu, India, 17-18 March 2016 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/2488 | - |
dc.description | Copyright belongs to proceeding publisher | en_US |
dc.description.abstract | The 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 image | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Haze removal | en_US |
dc.subject | Dark channel prior | en_US |
dc.subject | CLAHERGB | en_US |
dc.subject | Image Enhancement | en_US |
dc.title | Underwater Image Enhancement Based on Dark Channel Prior and Histogram Equalization | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
2016_ICIIECS_Mallik_Underwater.pdf | 1.44 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.