Abstract
This paper proposed a new method of underwater images restoration and enhancement which was inspired by the dark channel prior in image dehazing field. Firstly, we proposed the bright channel prior of underwater environment. By estimating and rectifying the bright channel image, estimating the atmospheric light, and estimating and refining the transmittance image, eventually underwater images were restored. Secondly, in order to rectify the color distortion, the restoration images were equalized by using the deduced histogram equalization. The experiment results showed that the proposed method could enhance the quality of underwater images effectively.
Highlights
This paper proposed a new method of underwater images restoration and enhancement which was inspired by the dark channel prior in image dehazing field
The images captured in water are usually blue or green, and the red channel intensity will be low in the whole picture; this leads to the problem that the dark channel image of degraded underwater image will not change with the imaging distance and the transmittance image is not related to the dark channel image
Our algorithm was inspired by the dark channel prior image dehazing
Summary
For the past several years, the attention of more and more scholars was drawn to the field of underwater images enhancement and restoration. Tan in [3] dehazed images by maximizing the local contrast of restoration images The result of this method was satisfying, but the saturation suffered from over enhancement. Galdran et al in [11] put forward an automatic red channel underwater image restoration method, and this method could be regarded as the deformation of the dark channel prior method. Our method could be regarded as the improved version of preciously reported dark channel prior Another bright channel prior based method different from the method proposed in this manuscript has been reported in [13]. The structure of this paper is as follows: in Section 2, the proposed image restoration and enhancement method is described, including bright channel image acquisition, the maximum color difference image acquisition, bright channel image correction, atmospheric light estimation, initial transmittance image acquisition, image restoration, and deduced histogram equalization.
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