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Method for smoothing self-regulation totality variation image base on edge confidence degree

A self-adjustment and confidence technology, applied in the field of image processing, can solve the problems of slow denoising speed and noise omission

Inactive Publication Date: 2009-04-15
HARBIN INST OF TECH
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Problems solved by technology

[0015] The purpose of the present invention is to provide a method that can effectively improve the shortcomings caused by the overall variational denoising model, such as slow denoising speed, step effect in the diffusion process, and easy noise omission. A self-adjusting total variational image smoothing method based on edge confidence to effectively remove noise and excessive texture information under the premise of region edges

Method used

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  • Method for smoothing self-regulation totality variation image base on edge confidence degree
  • Method for smoothing self-regulation totality variation image base on edge confidence degree
  • Method for smoothing self-regulation totality variation image base on edge confidence degree

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specific Embodiment approach

[0059] The method involved in this embodiment is realized by computer numerical calculation. The specific implementation is as follows:

[0060] (1) According to the selected local image size (choose m=2 in this embodiment, the selection of m is determined according to the compromise between calculation amount and smoothness, generally choose 2 or 3)), generate two one-dimensional sequences s(i ) and d(j), then obtain W=sd T and W T Two differential templates.

[0061] The two sequences used in this embodiment are:

[0062] s(i)=[0.0625 0.25 0.375 0.25 0.0625] T

[0063] d(j)=[-0.125 -0.25 0 0.25 0.125] T

[0064] thus have

[0065] W = sd T = - 0.0078 - 0.0156 0 0.0156 0.0078 ...

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Abstract

The invention provides a self-adjustment entire variational image smoothing method based on edge confidence level, is an entire variational image smoothing method containing self-adjustment factors; in the treatment process, based on a common image de-noising algorithm and an entire variational algorithm, a self-adjustment factor p function is added, thus realizing that smoothness level of local regions is ensured according to image local messages. The method can remove the noise and overcomplicated texture messages on the premise of better keeping the image edge, thus being capable of effectively overcoming the disadvantages of slow de-noising speed caused by an entire variational de-noising model, staircase effect produced in the diffusion process and noise missing which is caused easily. By using the method, the smoothness treatment is carried out on images with low signal-to-noise ratio; under the background of stronger noise, the noise and superfluous texture messages can be removed on the premise of keeping the region edges of interest.

Description

(1) Technical field [0001] The invention relates to the field of image processing, in particular to a method for denoising and smoothing an image with a low signal-to-noise ratio. (2) Background technology [0002] Image denoising is one of the important research topics in the field of image processing, and it is the basic link of image applications such as image segmentation, contour extraction, image compression and image reconstruction. Due to the low signal-to-noise ratio and complex image structure of many images, especially medical ultrasound images and remote sensing images, it is often necessary to do noise removal and smoothing preprocessing before image application. [0003] In 1977, A.N.Tikhonov proposed the image restoration algorithm: [0004] F ( μ ) = ∫ Ω | μ 0 - ...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 沈毅王艳李晓峰
Owner HARBIN INST OF TECH
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