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Image Denoising Method Based on Mathematical Morphology for Fourth Order Partial Differential Equation

A mathematical morphology and partial differential equation technology, applied in the field of fourth-order partial differential equation image denoising, can solve problems such as blurred edge details and achieve good visual effects

Active Publication Date: 2019-05-24
七腾机器人有限公司
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Problems solved by technology

However, the YK model tends to over-smooth the high-frequency components of the processed image, blur edge details, and produce isolated impulse noise, that is, point effects.

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  • Image Denoising Method Based on Mathematical Morphology for Fourth Order Partial Differential Equation
  • Image Denoising Method Based on Mathematical Morphology for Fourth Order Partial Differential Equation
  • Image Denoising Method Based on Mathematical Morphology for Fourth Order Partial Differential Equation

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Embodiment Construction

[0033] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings; it should be understood that the preferred embodiments are only for illustrating the present invention, rather than limiting the protection scope of the present invention.

[0034] A fourth-order partial differential equation image denoising method based on mathematical morphology, comprising the following steps: S1 adopts the method of mathematical morphology to detect the edge of the noise image; S2 calculates the gradient magnitude of the noise image; The morphological gradient operator and the gradient magnitude in step S2 establish a partial differential equation, and S4 adopts an iterative method to solve the partial differential equation to obtain a denoised image.

[0035] Mathematical morphology is a discipline based on strict mathematical theory. Its basic idea is to use certain structural elements to measure and extract the corres...

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Abstract

The invention discloses a fourth-order partial differential equation image denoising method based on mathematical morphology, which includes the following steps: S1 uses the method of mathematical morphology to detect the edge of the noise image; S2 calculates the gradient amplitude of the noise image; S3 according to The gradient operator of mathematical morphology in step S1 and the gradient amplitude in step S2 establish a partial differential equation. S4 uses an iterative method to solve the partial differential equation to obtain a denoised image. The present invention performs image denoising based on the fourth-order partial differential equation of mathematical morphology, which better maintains the edges of the processed image and has better visual effects.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a fourth-order partial differential equation image denoising method based on mathematical morphology. Background technique [0002] In order to obtain good image quality, image denoising has become a basic task of image processing, and image denoising methods based on partial differential equations (PDEs) have been widely used in image processing in recent years. [0003] Perona and Malik (PM) proposed a classic anisotropic diffusion model in 1990, which controls the diffusion degree of the image through the diffusion function of the image gradient value, and has a good denoising effect. In addition to the PM model, other models based on partial differential equations such as the TV model, their variational nature is second-order partial differential. Although the second-order model has a good effect on image denoising, the processed image will have obvious block effe...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T7/00
CPCG06T2207/20192G06T5/70
Inventor 仲元红张顺欧翔周瑶雷绮仑张钊源杨萍李瑾
Owner 七腾机器人有限公司
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