Improved wavelet transform and convolutional neural network image denoising method

A convolutional neural network and wavelet transform technology, which is applied in the field of image denoising, can solve the problems of singleness of noise removal and reduction of available information in images, and achieve the effect of reducing high-density noise and reducing noise.

Pending Publication Date: 2021-08-13
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0006] In order to overcome the singleness of traditional image denoising methods in terms of noise removal and the reduction of available image information in high-noise environments, the present invention provides an image denoising method based on wavelet transform and convolutional neural network. Allows two denoising algorithms to be combined, improving the network performance of the denoising algorithm

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  • Improved wavelet transform and convolutional neural network image denoising method

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[0029] In order to make the object, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0030] refer to Figure 1 ~ Figure 3 , an image denoising method based on the combination of wavelet transform and convolutional neural network. In order to improve the fitting ability of the image denoising network and accelerate the convergence of the network, first input the image containing noise, and obtain the image containing noise through stationary wavelet transform The wavelet coefficients of the deep convolutional neural network are obtained, and then the convolution layer is used to extract the image features of the input image, and the sample training and learning are performed to find the nonlinear mapping relationship between the noise image and the noise-free image wavelet coefficient, and then Perform image feature reconstruction, ...

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Abstract

The invention discloses an improved wavelet transform and convolutional neural network image denoising method. The method comprises the following steps of 1, performing size normalization, noise addition and data expansion on an original digital image; 2, constructing an image denoising network model WTCNN, constructing a wavelet coefficient model in order to obtain features of a noise-containing image, transforming the input noise-containing image into wavelet coefficients of different sub-bands by adopting stationary wavelet transform SWT, obtaining input data of a convolutional neural network, and then constructing a model structure combining two image denoising algorithms; and 3, performing simulation denoising on a noise-containing image in a real scene through the ideal denoising model obtained in the step 2, and obtaining a denoised image. According to the invention, the network performance of the denoising algorithm is improved.

Description

technical field [0001] The invention belongs to the field of digital image processing, in particular to an image denoising method. Background technique [0002] Digital image has become one of the important data carriers in today's society due to its excellent characteristics of carrying a large amount of information and being easy to transmit. At the same time, with the rapid development of digital image technology, people's requirements for image quality are increasing. More and more Researchers and engineers are working hard on how to generate finer and better-quality images to meet people's demand for high-quality images. Image denoising (Image denoising) is to use various technical means to filter or suppress the noise in the image to improve the quality of the image, so that the image can express richer information more accurately, and provide information for subsequent image segmentation, target recognition, etc. The image processing link provides the basis. As many...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/04G06N3/08
CPCG06T5/002G06N3/08G06T2207/20064G06N3/045
Inventor 谢琪管秋胡海根周乾伟徐新黎韦子晗徐涵杰
Owner ZHEJIANG UNIV OF TECH
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