Denoising for variable density ESPI fringes in nondestructive testing by an adaptive multiscale morphological filter based on local mean

Document Type

Article

Publication Date

10-1-2019

Abstract

Analysis of speckle images with variable density fringes is a challenging task when electronic speckle pattern interferometry (ESPI) is used for nondestructive testing of defects. In this paper, an adaptive multiscale morphological filter based on local mean is proposed. First, the image is segmented, and the regions are divided into different density levels using local mean. Then, the structural elements that adapt to different density levels are designed, and the proper size of the structural elements is determined by an iterative procedure. Finally, the morphological open–closing filtering is conducted, and the block edges are smoothed by averaging. The proposed method was applied to computer-simulation fringes and fringes experimentally obtained from a prefabricated defect specimen under thermal loading and then compared with the commonly used methods, i.e., discrete cosine filter, wavelet filter, Lee filter, and nonlocal mean filter. The experimental results showed that the proposed method had the best performance in terms of noise reduction and edge preservation. With the capability of noise reduction for ESPI images of variable density fringes, the proposed method will be helpful to build a quantitative relationship between fringes and defects in the cases of nonuniform deformation of speckle interferometry, such as nondestructive defect detecting, thermal structural analysis, and heterogeneous materials mechanical analysis.

Identifier

85072772085 (Scopus)

Publication Title

Applied Optics

External Full Text Location

https://doi.org/10.1364/AO.58.007749

e-ISSN

21553165

ISSN

1559128X

PubMed ID

31674457

First Page

7749

Last Page

7759

Issue

28

Volume

58

Grant

2011YQ14014507

Fund Ref

Ministry of Education of the People's Republic of China

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