Image denoising method and device based on Jacobian dynamic approximation

An image and dynamic technology, applied in the field of computer vision, to improve the visual experience, improve synthetic noise and real noise, and improve denoising performance

Pending Publication Date: 2022-05-06
UNIV OF SCI & TECH BEIJING
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention aims at the problem of how to better remove the synthetic noise and real noise in the noisy image and improve the user's visual experience in the prior art, and proposes the present invention

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  • Image denoising method and device based on Jacobian dynamic approximation
  • Image denoising method and device based on Jacobian dynamic approximation
  • Image denoising method and device based on Jacobian dynamic approximation

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Embodiment Construction

[0082] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0083] Such as figure 1 As shown, the embodiment of the present invention provides an image denoising method based on Jacobian dynamic approximation, which can be implemented by electronic devices. Such as figure 1 The shown flow chart of the image denoising method based on Jacobian dynamic approximation, the processing flow of the method may include the following steps:

[0084] S1. Acquire an image to be denoised.

[0085] S2. Input the image to be denoised to the shallow feature extraction unit of the image denoising network to obtain a shallow feature image.

[0086] Optionally, the shallow feature extraction unit in S2 is a 3×3 convolutional layer.

[0087] In a feasible implementation manner, a 3×3 convolutional layer is used to extract shallow...

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Abstract

The invention discloses an image denoising method and device based on Jacobian dynamic approximation, and relates to the technical field of computer vision. Comprising the steps of obtaining a to-be-denoised image; inputting an image to be denoised into a shallow feature extraction unit of the image denoising network to obtain a shallow feature image; inputting the shallow feature image into a denoising unit of an image denoising network to obtain a denoised image; and inputting the denoised image into a double-attention unit of an image denoising network to obtain a final denoised image. According to the method, an end-to-end image denoising network based on Jacobian dynamic approximation is constructed, and an ordinary differential equation solving module based on a Jacobian matrix is designed to realize forward derivation of a neural network. The method can be successfully applied to image denoising of synthetic noise and real noise, and compared with a classic image denoising method, the method has the advantage that the denoising performance can be obviously improved in the subjective and objective quality aspects of a reconstructed image.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to an image denoising method and device based on Jacobian dynamic approximation. Background technique [0002] In the process of image acquisition or processing, due to equipment limitations and environmental influences, the acquired images often inevitably introduce different degrees of noise, which greatly reduces the visual quality of the image, thereby limiting the performance improvement of computer vision tasks. Therefore, image denoising is one of the important research contents in the field of computer vision, and has attracted extensive attention from industry and academia. [0003] According to noise characteristics, traditional image denoising methods mainly include image noise filtering algorithms based on spatial domain or frequency domain. Spatial filtering mainly designs filters based on the difference between noise pixels and image pixels, such as Gaussian f...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06N3/04
CPCG06T2207/20081G06N3/045G06T5/70
Inventor 姚超班晓娟王笑琨
Owner UNIV OF SCI & TECH BEIJING
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