A Novel and Optimized Sine–Cosine Transform Wavelet Threshold Denoising Method Based on the sym4 Basis Function and Adaptive Threshold Related to Noise Intensity

Author:

Guo Yinhui1ORCID,Zhou Xinda1,Li Jie1,Ba Rongsheng1,Xu Zhaorui2,Tu Shuai1,Chai Liqun1

Affiliation:

1. Laser Fusion Reasearch Center, China Academy of Engineering Physics, Mianyang 621900, China

2. State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China

Abstract

In digital shearography, the speckle noise of the phase fringe pattern has a negative effect on the accuracy and reliability of the phase unwrapping procedure. A novel and optimized sine–cosine transform wavelet threshold denoising method is proposed to suppress speckle noise. Fast phase denoising can be achieved by using the proposed method while preserving the phase reversal information. The details of the selected wavelet basis function, the optimal decomposition level, the threshold function, and the denoising threshold are also provided in this manuscript. In particular, the decomposition level is analyzed and optimized through simulation analysis according to the speckle suppression index and the adaptive denoising method. The experimental results show that the proposed method has more adaptive ability in practical application than the sine–cosine transform average denoising method with the selected mask and iterative procedure, which speeds the denoising process up and takes better-unwrapped phase patterns.

Funder

National Natural Science Foundation of China

Local Science and Technology Development Fund Projects Guided by the Central Government, China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference26 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3