BayWT Image Fusion Method for Enhancement of Eddy Current Sub-surface Defect Images

Eddy current (EC) testing is one of the mostly used non-destructive evaluation (NDE) techniques for detection and imaging of defects in conducting material. The process of combination of the multiple images in to a single image to get the clear information is called image fusion. In this paper, wave...

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Bibliographic Details
Published in:SN computer science 2023-11, Vol.4 (6), p.837, Article 837
Main Authors: Soni, Anil Kumar, Soni, Aradhana, Tamrakar, Chandan
Format: Article
Language:English
Subjects:
Advances in Machine Vision and Augmented Intelligence
Computer Imaging
Computer Science
Computer Systems Organization and Communication Networks
Computer vision
Data Structures and Information Theory
Decomposition
Defects
Eddy current testing
Eddy currents
Entropy
Image enhancement
Information Systems and Communication Service
Methods
Nondestructive testing
Original Research
Pattern Recognition and Graphics
Performance evaluation
Probability
Signal to noise ratio
Software
Software Engineering/Programming and Operating Systems
Standard deviation
Statistical inference
Steel plates
Surface defects
Vision
Wavelet transforms
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Summary:Eddy current (EC) testing is one of the mostly used non-destructive evaluation (NDE) techniques for detection and imaging of defects in conducting material. The process of combination of the multiple images in to a single image to get the clear information is called image fusion. In this paper, wavelet transform and Bayesian principle-based image fusion method (BayWT) is proposed for enhancement of detectability and signal-to-noise ratio (SNR) of EC defect images. BayWT is used for fusion of EC sub-surface defect images generated at different frequencies from AISI type 304L stainless steel plate. The proposed fusion method is evaluated using different image metrics (i.e. SNR, entropy, standard deviation and fusion mutual information) and achieved three-time additional SNR. The performance of the BayWT fusion method is also compared with the commonly used NDE image fusion methods.
ISSN:2661-8907
2662-995X
2661-8907
DOI:10.1007/s42979-023-02310-1