Underwater image restoration and denoising method

Abstract

A method for restoring and denoising underwater image is provided. A single underwater image restoration algorithm is provided based on non-local prior. The dark channel priori algorithm is used to estimate the background light of the scene, and then a non-local priori model satisfying the imaging characteristics of underwater images is constructed by using the relationship between the wavelengthof the color light and the scattering coefficient, and the transmittance of different color light is estimated accordingly. The image is then optimized by pilot filtering, and the restoration and denoising characteristics are synchronously achieved. Finally, we use the guided filter to thin the transmittance and solve the minimal optimization problem of image restoration and perform denoising, andget the clear restoration results. On the basis of ensuring the operation efficiency, the invention effectively removes noise and can be effectively used in the engineering practice of underwater image restoration and denoising.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an underwater image restoration and denoising method. Background technique [0002] In recent years, with the development of marine resources, underwater images have been widely used in marine environment monitoring, underwater resource exploration, underwater biological science and many other fields. However, when light propagates underwater, due to the selective absorption of light by water, the phenomenon of medium scattering, and the complex environment in water, the quality of underwater images is seriously degraded, with the disadvantages of high blur, low contrast, and large noise, which seriously affects the quality of underwater images. Accurate acquisition of the following information. How to quickly restore underwater images, eliminate blur, remove noise, and improve clarity is of great significance. [0003] At present, a series of underwater image restoration method...

AI Technical Summary

Problems solved by technology

In the prior art, the restoration algorithm based on dark channel prior is ultimately based on local pixel prior information for restoration, and the result is prone to block effects, and the restoration process does not consider the noise of underwater imaging, and it cannot be restored while removing noise

On the other hand, the image restoration method based on non-local color prior was proposed by Berman in 2016. It uses the non-local characteristics of the corresponding lines in the color space to estimate the transmittance after degrading the pixels with similar colors in the clear image. , so as to effectively restore the image, but this algorithm is only suitable for atmospheric imaging models, not for underwater imaging models, and the algorithm also cannot remove noise

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