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Image de-noising method based on anisotropic diffusion of image entropy and PCNN

An anisotropy and image entropy technology, applied in the field of image processing, can solve the problems of not being able to preserve edge features and not be able to detect effectively, and achieve the effect of improving edge detection capabilities and avoiding errors

Active Publication Date: 2015-10-28
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0004] Image denoising based on partial differential equations Diffusion strength usually uses gradient information to detect edges, but when the edge part is heavily polluted by noise, these methods cannot effectively detect these edges, and thus cannot preserve the features contained in the edge

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  • Image de-noising method based on anisotropic diffusion of image entropy and PCNN
  • Image de-noising method based on anisotropic diffusion of image entropy and PCNN
  • Image de-noising method based on anisotropic diffusion of image entropy and PCNN

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Embodiment Construction

[0038] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0039] Pulse Coupled Neural Network (PCNN) is widely used in image processing fields such as image smoothing, image segmentation and edge detection, and has shown its superiority. PCNN model such as figure 1 As shown, its discrete mathematics iterative equation is as follows:

[0040] F i j ( n ) = e - α F F i j ( n - 1 ) + V F Σ k l M i ...

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Abstract

The invention discloses an image de-noising method based on anisotropic diffusion of image entropy and PCNN. The method comprises the steps as follows: firstly, processing a noise image with a pulse coupling neural network to obtain a entropy sequence En; using the En as an edge detection operator; then searching an optimal threshold to obtain an optimal de-noising threshold value k; finally de-noising the image by using an improved anisotropic diffusion model according to the obtained edge detection operator En and the optimal de-noising threshold value k. The method of the invention not only could effectively remove the image noise, but also could completely hold the area information of the image simultaneously.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image denoising method based on PCNN and anisotropic diffusion of image entropy. Background technique [0002] In the field of image processing and computer, image denoising is one of the most basic problems. The partial differential equation (Partial Differential Equation, PDE) can reflect the constraint relationship between the derivative of the unknown variable with respect to time and the derivative with respect to space variables. The image is processed by using the complete numerical analysis theory of partial differential equations, so the method based on partial differential equations has been widely used in image denoising. [0003] In the early 1990s, foreign scholars Perona and Malik proposed the classic anisotropic diffusion PM model for the first time. This model controls the diffusion degree of the image by a diffusion function about the ima...

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Application Information

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IPC IPC(8): G06T5/00G06T7/00
CPCG06T2207/20192G06T5/70
Inventor 周先春吴婷石兰芳陆传荣周林锋
Owner NANJING UNIV OF INFORMATION SCI & TECH
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