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
View PDF0 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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 diffu

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • 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

Examples

Experimental program
Comparison scheme
Effect test

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 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T5/00
Inventor 沈毅王艳李晓峰
Owner HARBIN INST OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products