Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Wavelet Denoising Method with Variable Threshold

A technology of wavelet denoising and thresholding, applied in image enhancement, image analysis, instruments, etc.

Active Publication Date: 2021-10-12
ANHUI UNIV OF SCI & TECH
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method organically combines soft and hard threshold functions together, and achieves a good denoising effect and improves the signal-to-noise ratio of the image, but it still cannot solve the shortcomings of the soft and hard threshold functions themselves.

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
  • A Wavelet Denoising Method with Variable Threshold
  • A Wavelet Denoising Method with Variable Threshold
  • A Wavelet Denoising Method with Variable Threshold

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0054] figure 1 with figure 2 They are the hard and soft threshold function diagrams of wavelet respectively. When it is used for image denoising, because the hard threshold function is discontinuous at the threshold point, the reconstructed image will appear pseudo-Gibbs effect, ringing and other visual distortion. However, there is a constant deviation between the wavelet signal processed by the soft threshold function and the wavelet signal of the origin...

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 discloses a wavelet denoising method with variable threshold, which includes five steps. Step 1, input the original image and add the corresponding Gaussian noise; Step 2, select the wavelet basis function and determine the number of layers O of wavelet decomposition: decompose the noise image S to obtain the first layer of low-frequency coefficients A1, horizontal and vertical high-frequency coefficients H1 and V1, diagonal high-frequency coefficient D1; decompose A1 to obtain the second-layer low-frequency coefficient A2, horizontal and vertical high-frequency coefficients H2 and V2, and diagonal high-frequency coefficient D2; decompose A2 to obtain the third-layer low-frequency coefficient A3, horizontal and Vertical high-frequency coefficient H3 and V3 and diagonal high-frequency coefficient D3; Decompose to the Oth layer successively; Step 3, select the combined wavelet threshold value and the wavelet threshold value function with straight line as asymptotic line to process wavelet coefficient; Step 4, to The wavelet coefficients after threshold quantization are reconstructed by wavelet; Step 5, outputting the image after denoising. The invention can improve the precision of noise signal processing by wavelet transform, effectively improve the denoising effect of images, and obtain high-quality denoising images.

Description

technical field [0001] The invention relates to the denoising field of digital image processing, in particular to a wavelet denoising method with variable threshold. Background technique [0002] During the formation, recording, processing and transmission of images, they are easily affected by noise, which leads to the degradation of image quality, makes the image blurred, and even submerges image features. posed difficulties. Therefore, before image processing, noise removal is a key preprocessing link. In order to obtain high-quality digital images, it is necessary to denoise the images, to keep the integrity of the original information (that is, the main features) as much as possible, and to remove useless information in the signal. Therefore, noise reduction processing has always been a hot spot in image processing. [0003] Wavelet denoising is generally divided into three categories. The first category is to use the wavelet transform modulus maximum method for imag...

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 Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/20064
Inventor 赵佰亭王风郭永存贾晓芬黄友锐
Owner ANHUI UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com