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Image smoothing method based on quasi-normal distribution

An image smoothing and image technology, applied in the field of image processing, can solve the problems of unstable image noise reduction, poor edge preservation, "staircase" effect, etc., achieving less information, improved peak signal-to-noise ratio, and reduced processing effect of time

Active Publication Date: 2017-05-17
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

With the continuous deepening of research on this technology, many experimental results show that the PM algorithm has defects, the processed image noise reduction is unstable, there is an obvious "ladder" effect, and the edge preservation is not very good

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  • Image smoothing method based on quasi-normal distribution
  • Image smoothing method based on quasi-normal distribution
  • Image smoothing method based on quasi-normal distribution

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[0023] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0024] The diffusion equation of the traditional PM algorithm is In the formula, div, are divergence operator and gradient operator respectively, I 0 Represents the initial image, I is obtained by convolving the initial image with the Gaussian kernel, that is, I(x,y,t)=I 0 *G(x,y,t), its diffusion coefficient Variation curve such as figure 1 shown. Generally speaking, point A corresponds to the texture area of ​​the image; point B corresponds to the flat area of ​​the image, which needs to be strengthened; point C corresponds to the edge area of ​​the image, and the intensity of denoising n...

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Abstract

The invention relates to an image smoothing algorithm based on quasi-normal distribution. The image smoothing algorithm comprises the following steps: step one, carrying out Gauss filtering on noise images and removing louder noise; step two, introducing a diffusion coefficient expressed by a formula as shown in the description of a PM algorithm; step three, introducing a flux function into the quasi-normal distribution process in order to preserve texture; step four, horizontally moving a curve of g1 in the step two rightwards by c (c is greater than 0) to obtain a formula as shown in the description; step five, further processing the image by using a semi-implicit additive operator splitting (AOS) algorithm, and carrying out repeated iteration to obtain a clear image. According to the image smoothing algorithm based on quasi-normal distribution, the diffusion process can be stably controlled; the detail information aspects of noise removal, edge preserving and texture preserving of the images reach the satisfactory effects; the peak signal to noise ratio is greatly increased.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image smoothing algorithm based on quasi-normal distribution. Background technique [0002] Digital images are the source of information in many disciplines, but images often introduce noise due to various reasons during the acquisition process. Therefore, in the field of image processing and computer, image denoising is one of the most fundamental problems. In recent decades, partial differential equation (PDE) methods have been widely used in image processing, and significant progress has been made in image denoising, segmentation, edge detection, and enhancement. Among image processing methods based on partial differential equations, anisotropic diffusion has become a research hotspot because of its high-quality processing results. Since the PM algorithm was proposed, anisotropic diffusion technology has made great progress. With the continuous deepening of the ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 周先春汪美玲周林锋石兰芳
Owner NANJING UNIV OF INFORMATION SCI & TECH
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