Image fusion denoising method and system based on u-net and pyramid module
An image fusion and pyramid technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problem of not being able to preserve image details well, achieve high practicability, improve denoising performance, and broad application prospects
Active Publication Date: 2022-06-14
FUZHOU UNIV
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Problems solved by technology
Although the denoising results of deep learning methods are better than those of traditional methods, most of the current methods still have the problem of not being able to preserve image details well, and the denoising results obtained after denoising with different intensities on the same noisy image Images have different performances in texture-rich regions and texture-smooth regions, and effective image fusion can better preserve image details
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[0045] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0046] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0047] It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and / ...
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The present invention relates to a kind of image fusion denoising method and system based on U-Net and pyramid module, the method comprises the following steps: S1, carry out preprocessing with paired original noise image and noise-free image, obtain paired for training Image block; S2, select the image denoising depth network model FFDNet, and load the model parameters that have been trained; step S3, build an image fusion denoising network based on U‑Net and pyramid modules; S4, use batches as units to pair Input the image block into FFDNet, and input the obtained result into the image fusion denoising network, train the image fusion denoising network according to the loss function; S5, input the original noise image for testing into FFDNet, and input the obtained result into the training The image fusion denoising network to get the final denoising image. The method and system are beneficial to improving the denoising performance and retaining more image details.
Description
technical field [0001] The invention belongs to the technical field of image and video processing, and in particular relates to an image fusion denoising method and system based on U-Net and pyramid modules. Background technique [0002] In recent years, with the continuous advancement of technology and the continuous upgrading of mobile digital devices, people's access to information has become easier and faster. Compared with text, images are one of the most intuitive ways for people to obtain information. In a clear image, the outline of the object is clear, the foreground and background of the image are clearly visible, and people can accurately classify the image content and identify objects. However, in the process of image acquisition, the quality of the generated image is often degraded due to the interference of some different types of external factors, such as camera shake and signal disturbance, and this degradation is irreversible. The degraded image greatly af...
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IPC IPC(8): G06T5/00G06T5/50G06N3/08
CPCG06T5/50G06N3/084G06T2207/20016G06T2207/20021G06T2207/20081G06T2207/20084G06T2207/20221G06T5/70
Inventor 陈羽中沈启金牛玉贞陈钧荣
Owner FUZHOU UNIV