结合背景光融合及水下暗通道先验和色彩平衡的#br# 水下图像增强

doi:10.16451/j.cnki.issn1003-6059.201809008

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Abstract

Different hues, contrasts and blurriness of underwater images are caused by underwater environment, light attenuation and photography methods. The dark channel prior(DCP) or the maximum intensity prior(MIP) is often utilized in the underwater image restoration methods based on the image formation model(IFM). Low-quality restored images are produced by these methods, and they are easily disturbed by the complicated underwater environment. The method of image restoration using background light fusion and underwater DCP and image color balancing for underwater image enhancement is proposed in this paper. Firstly, a correct background light(BL) is estimated through the fusion of multiple candidate background lights.Then, an underwater dark channel prior(UDCP) is determined based on the statistics of a large number of high-quality(HQ) underwater images and accurate RGB transmission maps are finally obtained. The restored image in the RGB color model is transformed to a CIE-Lab color model, and the ‘L’ luminance component and color components ‘a’ ‘b’ are conducted with the normalized stretching and optimal modification respectively to further improve the brightness and contrast of the restored image. Various qualitative and quantitative assessments are applied to demonstrate that the proposed method is better than the state-of-the-art restoration methods in contrast, brightness and color.

Key words： Underwater Image Enhancement Background Light Fusion Underwater Dark Channel Prior(UDCP) Image Formation Model(IFM) Color Balancing

Received: 02 May 2018

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	Articles by authors
	SONG Wei
	WANG Yan
	HUANG Dongmei
	HE Qi
	WANG Zhenhua

Cite this article:

SONG Wei,WANG Yan,HUANG Dongmei等. Combining Background Light Fusion and Underwater Dark Channel Prior with Color Balancing for Underwater Image Enhancement[J]. , 2018, 31(9): 856-868.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201809008 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I9/856

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