Image denoising method based on Shearlet contraction and improved TV model

An image and model technology, applied in the field of image processing, can solve the problems of not being able to obtain better noise suppression and edge preservation effects at the same time, and achieve the effects of suppressing pseudo-Gibbs oscillation, low computational complexity, and noise removal

Active Publication Date: 2012-09-12
西安谦腾进科技有限公司
View PDF1 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In order to avoid the deficiencies of the prior art, the present invention proposes an image denoising method based on Shearlet contraction and improved TV model, which overcomes the disadvantages that the prior art methods cannot achieve better noise suppression and edge preservation effects at the same time

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
  • Image denoising method based on Shearlet contraction and improved TV model
  • Image denoising method based on Shearlet contraction and improved TV model
  • Image denoising method based on Shearlet contraction and improved TV model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0027] Step 1: For the original noisy image u 0 Carry out the Shearlet transform decomposition to obtain the high-frequency coefficient C of each scale H and low frequency coefficient C L , and divide the high frequency subbands.

[0028] Step 2: Use the Monte-Carlo method to estimate the noise variance for each scale subband, and then estimate the high frequency coefficient C of each scale H Perform hard thresholding to obtain the denoised high-frequency coefficient C H '.

[0029] Step 3: The high frequency coefficient C obtained in step 2 H ’ and the low-frequency coefficient C obtained in step 1 L Perform the Shearlet inverse transform to obtain the reconstructed image, and obtain the image u after the initial denoising 1 .

[0030] Step 4: Combining the improved total variation model for the initial denoising image u 1 Perform secondary denoising to...

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 relates to an image denoising method based on a Shearlet contraction and an improved TV model, wherein a TV-denoising model is improved and a novel mixed denoising method by combining the Shearlet contraction is proposed. The method organically combines the sparse representation capability of Shearlet for a high dimension function with the protection capability of the TV-denoising model for an edge, wherein the method obtains a first-denoising image through a hard threshold function contraction, and then improves fidelity terms of a total variation model, and then makes a second denoising of the false Gibbs effect of the first-denoising image by combing the improved total variation model. On the prerequisite of protecting important information such as edges, etc., the method effectively inhibits the false Gibbs oscillation caused by the Shearlet contraction, and realizes a better visual effect and a lower computation complexity.

Description

technical field [0001] The invention belongs to the technical field of image processing, and mainly relates to an image denoising method based on Shearlet contraction and improved TV model. Background technique [0002] Image denoising is a basic and extensive research topic in the field of computer vision and image processing. The key to denoising is to effectively suppress noise while maintaining important details in the image, such as textures and edges. Among various image denoising methods, the multi-scale geometric analysis method developed from wavelet theory and the denoising method based on partial differential equations have outstanding performance in the application of image denoising. [0003] At present, with the development of computational harmonic analysis techniques, multi-scale geometric analysis methods such as Curvelet transform, Contourle transform and Shearlet transform have been widely valued and studied in image denoising. Among them, the Shearlet tr...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 李映陈瑞鸣胡杰张艳宁
Owner 西安谦腾进科技有限公司
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap