17 July 2019 Underwater image enhancement and restoration based on local fusion
Yakun Gao, Jing Wang, Haibin Li, Lei Feng
Author Affiliations +
Abstract

Underwater imaging and image processing play important roles in oceanic scientific research. However, because the light is absorbed and scattered, the obtained underwater images are seriously degraded. Color distortion, low contrast, and detail (edge information) loss are the major problems of underwater images. We propose a method to solve these problems. First, a local adaptive proportion fusion algorithm is proposed to produce a color-balanced image, which is the first input image. Second, an edge-enhanced image is produced as the second input image. Third, a proportion fusion image is produced as the third input image. Finally, the image formation model-based local triple fusion method is used to merge these three input images and get the final result. Experimental results show that the proposed method could effectively balance color distortion and enhance edges of the degraded images. Subjective and objective evaluations show that our method is superior to many state-of-the-art methods.

© 2019 SPIE and IS&T 1017-9909/2019/$28.00 © 2019 SPIE and IS&T
Yakun Gao, Jing Wang, Haibin Li, and Lei Feng "Underwater image enhancement and restoration based on local fusion," Journal of Electronic Imaging 28(4), 043014 (17 July 2019). https://doi.org/10.1117/1.JEI.28.4.043014
Received: 14 January 2019; Accepted: 13 June 2019; Published: 17 July 2019
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CITATIONS
Cited by 11 scholarly publications.
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KEYWORDS
Image enhancement

Image fusion

Image restoration

Image filtering

Image quality

Image processing

Air contamination

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