Abstract
The quality of underwater images is an important problem for resource detection. However, the light scattering and plankton in water can impact the quality of underwater images. In this paper, a novel underwater image restoration based on non-convex, non-smooth variation and thermal exchange optimization is proposed. Firstly, the underwater dark channel prior is used to estimate the rough transmission map. Secondly, the rough transmission map is refined by the proposed adaptive non-convex non-smooth variation. Then, Thermal Exchange Optimization is applied to compensate for the red channel of underwater images. Finally, the restored image can be estimated via the image formation model. The results show that the proposed algorithm can output high-quality images, according to qualitative and quantitative analysis.
Highlights
With exploration and research in some underwater fields, such as oceans, lakes, and rivers, the application of underwater detection is more extensive, and the requirements for the quality of the captured images are much higher
The issue of improving underwater image quality was approached by the use of additional information, such as using multiple images [4] or polarization filters [5,6]
We propose a novel underwater image restoration algorithm based on dark channel prior (DCP) and non-convex and non-smooth variation to improve the underwater image quality and correct color
Summary
With exploration and research in some underwater fields, such as oceans, lakes, and rivers, the application of underwater detection is more extensive, and the requirements for the quality of the captured images are much higher. The IFM-free methods, such as Retinex [7], Gray-World algorithm [8], and multi-scale fusion [9,10], are called image enhancement methods, which improve the contrast without using underwater imaging models. These methods have high contrast and fast calculation speeds. In addition to red channel compensation, the optimization of transmission maps is an important research direction of IFM-based methods, which improves the contrast and corrects the color of restored images. We propose a novel underwater image restoration algorithm based on DCP and non-convex and non-smooth variation to improve the underwater image quality and correct color. Because the attenuation of absorption and scattering for red light is the fastest, there are errors when using the fastest attenuating channel (red channel) to estimate the transmission maps of other channels
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