Underwater image enhancement and restoration method based on convolutional neural network

Abstract

The invention discloses an underwater image enhancement and restoration method based on a convolutional neural network, and the method comprises the steps: degrading a plurality of conventional imagesthrough a to-be-processed underwater image, forming a training set through the plurality of conventional images and the corresponding degraded conventional images, and sequentially inputting the training set into the convolutional neural network for training; then, inputting the underwater image to be processed into the trained convolutional neural network, and outputting a first image; carryingout CIELAB color space transformation on the image, and extracting an L brightness channel, an A color channel and a B color channel of the image; and finally, performing texture enhancement on the to-be-processed underwater image, replacing the L brightness channel of the first image with the image after texture enhancement, and combining the image after texture enhancement with the A color channel and the B color channel in the first image to obtain a final image. According to the method, the problem of missing of underwater image training data is solved, complex calculation of a traditionalunderwater imaging model is avoided, and the quality of underwater images is well improved.

Description

technical field [0001] The invention relates to the field of underwater image enhancement and restoration, in particular to an underwater image enhancement and restoration method based on a convolutional neural network. Background technique [0002] Obtaining underwater images is of great significance to the detection and development of underwater environments. In the process of shooting underwater images, due to the rapid attenuation of red light during propagation, and the light scattering caused by particles in the water, the collected underwater images usually have low contrast, uneven brightness, unclear texture and chromatic aberration. Serious and other shortcomings. Therefore, people usually perform enhancement and restoration processing on underwater images to ensure the smooth development of underwater environmental operations. [0003] In recent years, underwater image processing technology has attracted more and more attention from scholars, and various underwa...

AI Technical Summary

Problems solved by technology

These methods have a certain effect on the color correction of underwater images and the improvement of texture clarity, but there are still subjective unnatural color differences and texture distortions.

Ancuti et al. proposed to fuse the parameters of the underwater images processed by the three methods of color improvement, gamma correction and texture enhancement, but this kind of algorithm is complex and the image is prone to artifacts caused by over-enhancement

In addition, traditional methods require a large amount of environmental data such as water scattering coefficients, scene depth, etc., which are difficult to obtain from a single image

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