End-to-end underwater image restoration method based on ambient light perception

Abstract

The invention discloses an end-to-end underwater image restoration method based on ambient light perception, and mainly solves the problem of poor color cast correction and sharpness processing effects during underwater image processing in the prior art. According to the scheme, the method comprises the following steps: respectively constructing an ambient light sensing network and a restoration subject network by using a Pytorch framework, and respectively constructing training sets B and C of the two networks; adopting an adaptive moment estimation algorithm to train an ambient light sensing network and a restoration subject network respectively by using B and C, inputting a to-be-processed image Ic into the trained ambient light sensing network, and outputting an ambient light value Ac; and inputting the Ac and the Ic into the trained restored subject network, and outputting a clear image Jc. The contrast of underwater images with different degradation degrees is improved, color cast can be effectively corrected, the peak signal-to-noise ratio, the structural similarity, the chromatic aberration formula, the non-reference image space quality evaluation and the underwater color image quality evaluation are all superior to those in the prior art, and the method can be used for clearness processing of the underwater images.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an underwater image restoration method, which can be used to process a single underwater image taken by an imaging system. Background technique [0002] Affected by water's absorption and scattering of light in real conditions, underwater optical images generally suffer from low contrast, color distortion, and quality degradation of image blur. These degraded images not only affect the subjective experience of human eyes, but also seriously restrict the performance of various intelligent visual information processing systems. Therefore, the reconstruction of clear underwater optical images has very important practical application value. At present, the key issue of underwater image processing methods is how to improve image clarity and correct color cast, which are mainly divided into four categories: traditional image enhancement, traditional image restorat...

AI Technical Summary

Problems solved by technology

The network design of this kind of method is relatively complicated, the learning difficulty is relatively large, and it is prone to difficult fitting problems, and this kind of method relies heavily on the distribution of training data, the generalization ability is insufficient, and the restoration effect for severely degraded underwater images is poor.

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