Denoising and contrast enhancement fusion based on white balance for underwater images

Chao Wei; Junfeng Wang; Guannan Chen

doi:10.1117/12.2539429

27 November 2019 Denoising and contrast enhancement fusion based on white balance for underwater images

Chao Wei, Junfeng Wang, Guannan Chen

Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 113210E (2019) https://doi.org/10.1117/12.2539429
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China

Abstract

When the scene reached the human eye or other sensor through the underwater medium, the original color property of the object could be basically lost, and the background of most images was blue-green. In this paper, to remove the blue-green color of the underwater image and increase the color contrast of the image, a novel fusion method of two images was proposed. The two images were derived from the filtering denoising result and the contrast enhancement result after whitebalancing version of the original degraded image. Then, based on the two images, the associated weight maps were designed to enhance edge texture and color contrast of the output image. Finally, to avoid artifacts in the reconstructed image, we adopted the multiscale fusion strategy to fuse the processed two images. Experiments showed that our algorithm achieved better image contrast and edge sharpness than other methods and obtained better exposure for darker areas of the image.

Citation Download Citation

Chao Wei, Junfeng Wang, and Guannan Chen "Denoising and contrast enhancement fusion based on white balance for underwater images", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113210E (27 November 2019); https://doi.org/10.1117/12.2539429

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