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An image fusion denoising method, device, and system

An image fusion and image technology, applied in the field of image processing, to achieve the effect of accurate denoising effect, ensure denoising quality, and accurate noise estimation

Active Publication Date: 2020-07-31
南京苏宁电子信息技术有限公司
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Problems solved by technology

[0004] In order to solve the technical problems existing in the existing denoising methods, the present invention provides an image fusion denoising method, device and system

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Embodiment Construction

[0061] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only Some, but not all, embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0062] Existing image denoising methods mainly include: denoising methods based on prior models, denoising methods based on filtering, and filtering methods based on deep learning. Among the above three commonly used denoising methods, the denoising method based on the prior model cannot meet the real-time image processing requirements, and the processing efficiency is...

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Abstract

The invention discloses an image fusion denoising method, device and system. The method includes: using a filtering algorithm to process a noise image to obtain a first denoised image, and using a residual image method to calculate the noise image and the first denoised image. , obtain the first noise residual image; use the first neural network model to process the noise image, obtain the second denoised image, use the residual image method to calculate the noise image and the second denoised image, and obtain the second noise residual image; The noise image, the first noise residual image and the second noise residual image are input into the second neural network model for fusion and denoising to obtain the target denoised image. The present invention uses a fusion method to combine the noise images processed by the collaborative filtering algorithm and the neural network model algorithm, thereby obtaining a target denoising image that takes into account both the denoising effect and image details, and better guarantees the quality of image denoising.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image fusion denoising method, device and system. Background technique [0002] Image noise is a random change of brightness or color information in an image, and the more noise there is in the image, the worse the imaging quality of the image is. Image noise will not only affect the visual understanding of image clarity and accuracy, but more importantly, it will affect the quality of high-level image processing such as edge detection, image segmentation, and feature matching. Therefore, in order to meet the technical requirements of further image processing, a variety of image denoising methods have emerged in this field, such as: filter-based BM3D, deep learning-based DNCNN, prior model-based WNNM and other denoising methods. [0003] However, the above denoising methods have their own insurmountable defects: the filter-based denoising method is designed f...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T2207/20024G06T2207/20081G06T2207/20084G06T2207/20221G06T2207/20021G06T5/70
Inventor 刘剑君
Owner 南京苏宁电子信息技术有限公司
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