A denoising method for underwater images based on generative confrontation network
An underwater image and network technology, applied in biological neural network models, image enhancement, image analysis, etc., can solve the problems of blurred image edge outline, reduced effectiveness, loss of detail information, etc., to achieve improved denoising effect and easy production , good denoising effect
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[0028] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0029] In order to overcome the problems that the underwater image noise is difficult to remove and the edge texture cannot be enhanced, the present invention proposes an underwater image denoising method based on a generative adversarial network. The method first inputs the retina-enhanced underwater image with noise into a generative network composed of several residual blocks, and obtains a feature map with three-channel (r, g, b three-channel) output; then the output The obtained feature map and the noise-free label image of Shimizu are respectively mapped to a deep feature space through the VGG-19 network (the network has been proposed and publicly used by Google), and the feature map and the noise-free label image of Shimizu are calculated in The perceptual cost in the deep feature space makes the feature map output by the generative network as cl...
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