Literature DB >> 28981416

Color Balance and Fusion for Underwater Image Enhancement.

Codruta O Ancuti, Cosmin Ancuti, Christophe De Vleeschouwer, Philippe Bekaert.   

Abstract

We introduce an effective technique to enhance the images captured underwater and degraded due to the medium scattering and absorption. Our method is a single image approach that does not require specialized hardware or knowledge about the underwater conditions or scene structure. It builds on the blending of two images that are directly derived from a color-compensated and white-balanced version of the original degraded image. The two images to fusion, as well as their associated weight maps, are defined to promote the transfer of edges and color contrast to the output image. To avoid that the sharp weight map transitions create artifacts in the low frequency components of the reconstructed image, we also adapt a multiscale fusion strategy. Our extensive qualitative and quantitative evaluation reveals that our enhanced images and videos are characterized by better exposedness of the dark regions, improved global contrast, and edges sharpness. Our validation also proves that our algorithm is reasonably independent of the camera settings, and improves the accuracy of several image processing applications, such as image segmentation and keypoint matching.

Year:  2017        PMID: 28981416     DOI: 10.1109/TIP.2017.2759252

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


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2.  A Underwater Sequence Image Dataset for Sharpness and Color Analysis.

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5.  Study on the Classification Performance of Underwater Sonar Image Classification Based on Convolutional Neural Networks for Detecting a Submerged Human Body.

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Journal:  Sensors (Basel)       Date:  2020-11-04       Impact factor: 3.576

10.  The Color Improvement of Underwater Images Based on Light Source and Detector.

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Journal:  Sensors (Basel)       Date:  2022-01-17       Impact factor: 3.576

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