An image denoising model training method, system, device, and computer medium

Abstract

The application discloses an image denoising model and its training method, system, equipment, and computer media, and obtains a noise image training set, which includes an initial noise image and an initial denoising image corresponding to the initial noise image; training based on noise images The initial image denoising model is trained to obtain the trained image denoising model, and the target noise image is denoised based on the trained image denoising model; wherein, the image denoising model includes 15 layers connected in sequence The neural network layer, the first neural network layer and the eighth neural network layer are composed of convolutional layers; the second neural network layer to the seventh neural network layer are all composed of convolutional layers, WN layers and activation function layers; The ninth neural network layer to the fourteenth neural network layer are composed of convolutional layer, WN layer and activation function layer; the fifteenth neural network layer is composed of dropout layer and convolutional layer. Improved image denoising efficiency.

Description

technical field [0001] The present application relates to the technical field of neural network models, and more specifically, relates to an image denoising model and a training method, system, device, and computer medium. Background technique [0002] With the development of information technology and Internet technology, image processing technology has also been successfully applied to programs including disaster relief, weather forecasting, photo entertainment, face recognition, and fast payment for shopping. However, during the process of image collection, storage, transmission, processing and imaging by the camera, it is easily affected by factors such as rainy weather, foggy weather, poor lighting conditions, camera shake, etc., making the captured image unclear. In order to ensure the imaging effect of the image, it is necessary to restore the unclear image to a clear image, that is, it is necessary to perform image denoising processing on the unclear image. [0003]...

AI Technical Summary

Problems solved by technology

[0004] However, in the existing image denoising methods, it is necessary to combine the discriminant method and the optimization method to improve the denoising performance, which makes the image denoising efficiency low

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