Abstract
The quality of underwater images is often affected by the absorption of light and the scattering and diffusion of floating objects. Therefore, underwater image enhancement algorithms have been widely studied. In this area, algorithms based on Multi-Scale Retinex (MSR) represent an important research direction. Although the visual quality of underwater images can be improved to some extent, the enhancement effect is not good due to the fact that the parameters of these algorithms cannot adapt to different underwater environments. To solve this problem, based on classical MSR, we propose an underwater image enhancement optimization (MSR-PO) algorithm which uses the non-reference image quality assessment (NR-IQA) index as the optimization index. First of all, in a large number of experiments, we choose the Natural Image Quality Evaluator (NIQE) as the NR-IQA index and determine the appropriate parameters in MSR as the optimization object. Then, we use the Gravitational Search Algorithm (GSA) to optimize the underwater image enhancement algorithm based on MSR and the NIQE index. The experimental results show that this algorithm has an excellent adaptive ability to environmental changes.
Highlights
IntroductionBut the marine environment is complicated, and underwater exploration by humans is difficult
Marine resources are abundant, but the marine environment is complicated, and underwater exploration by humans is difficult
There are two other important research directions in this field: algorithms based on the Dark Channel Prior (DCP) algorithm and algorithms based on the Generative Adversarial Networks (GAN)
Summary
But the marine environment is complicated, and underwater exploration by humans is difficult. HE transforms the original image into an output image with roughly the same number of pixels at most gray levels through pixel value transformation This algorithm has a simple structure and low computation, but HE is not good at improving the local contrast of the image. There are two other important research directions in this field: algorithms based on the Dark Channel Prior (DCP) algorithm and algorithms based on the Generative Adversarial Networks (GAN) He et al proposed the DCP [21] algorithm, which has been widely used in the field of image enhancement [22,23] due to its simple defogging model and good defogging effect. The existing underwater image enhancement algorithms use fixed parameters They can improve the visual quality of underwater images to some extent, there are problems of amplified noise and color distortion. Eng. 2020, 8, 741 each workflow; Section 3 briefly introduces relevant background knowledge; Section 4 introduces the selection method of the parameters and the no reference image quality assessment index; Section 5 introduces the main work content of this article; Section 6 conducts experiments on the algorithm proposed in this article and objectively analyzes its performance; and Section 7 presents the conclusion of the article
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