融合暗原色先验和稀疏表示的水下图像复原

doi:10.11999/JEIT170381

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Abstract Due to the influences of scattering of the light and interference of the noise, underwater image quality is always degraded severely. In order to remove the blur and suppress the noise, and improve the quality of underwater image, a novel underwater image restoration method based on the combination of dark-channel prior with sparse representation is proposed. This method adopts the dark-channel prior theory to calculate the dark-channel image at first, and then uses sparse representation to denoise and optimize the dark-channel image. Based on the improved dark-channel image, the more precise water transmissivity and light intensity can be achieved to compute the final restoration result, effectively eliminating the image blur as well as noise. The experimental results show that the proposed method can effectively improve the image factors, such as average gradient and entropy, so as to compensate the degraded image.

Key words： Underwater image restoration Dark-channel prior Sparse representation

Received: 25 April 2017 Published: 01 November 2017

PACS:

TP391

Fund:The National Natural Science Foundation of China (61374019, 61603124), The Fundamental Research Funds for the Central Universities (2015B19014), 333 High-Level Talent Training Program of Jiangsu Province, Six Talents Peak Project of Jiangsu Province (XYDXX-007)

Corresponding Authors: WANG Xin E-mail: wang_xin@hhu.edu.cn

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	WANG Xin
	ZHU Hangcheng
	NING Chen
	Lü Guofang

Cite this article:

WANG Xin,ZHU Hangcheng,NING Chen等. Combination of Dark-channel Prior with Sparse Representation for Underwater Image Restoration[J]. JEIT, 2018, 40(2): 264-271.

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http://jeit.ie.ac.cn/EN/10.11999/JEIT170381 OR http://jeit.ie.ac.cn/EN/Y2018/V40/I2/264

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