Electrical Tree Image De-Noising using Threshold Wavelet Transform and Wiener Filter

Abdulah, Cik Siti Khadijah; Gazata, Nur Dini Athirah; Rohani, Mohamad Nur Khairul Hafizi; Ismail, Baharuddin; Mohd Isa, Mohd Anuar; Rosmi, Afifah Shuhada; Mansor, Noor Syazwani; Jamil, Mohamad Kamarol; Muhammad-Sukki, Firdaus; Mas'ud, Abdullahi A.

Abstract

Electrical treeing occurred in solid dielectric materials, especially in electrical application with high voltage. The occurrence of electrical tree happens when high electric fields applied, causing tiny channels or paths to form. The main issue during the data collection process is the changes of lighting, making it difficult to study the tree's propagation length, fractal dimension, and growth rate due to corrupted images. This research aims to analyse electrical tree structure images in XLPE material using a CCD camera and develop image de-noising techniques to suppress noise on the electrical tree image. The performance was then analysed using the Otsu thresholding algorithm for accurate segmentation. The methodology was divided into four phases: sample preparation, experimental setup, image pre-processing in MATLAB, and testing four de-noising filters: Wiener, median, NLM, and Gaussian. The Wiener filter with higher PSNR, SNR, and RMSE was selected and using superimposed method, both threshold wavelet transforms and wiener was combined to eliminate the noise. Finally, the proposed method of superimposed was tested with the Otsu thresholding method to evaluate accuracy, sensitivity, and specificity of the combination filter. Based on the analysis of PSNR, SNR, and RMSE, the performance of the threshold wavelet and Wiener filter (TWWF) de-noising technique improves the image quality of the electrical tree structure. Thus, for the Otsu thresholding segmentation algorithm analysis, it also had the highest values in terms of accuracy, sensitivity, and specificity.

Citation

Abdulah, C. S. K., Gazata, N. D. A., Rohani, M. N. K. H., Ismail, B., Mohd Isa, M. A., Rosmi, A. S., Mansor, N. S., Jamil, M. K., Muhammad-Sukki, F., & Mas'ud, A. A. (2025). Electrical Tree Image De-Noising using Threshold Wavelet Transform and Wiener Filter. Journal of Advanced Research in Applied Sciences and Engineering Technology, 53(1), 73-85. https://doi.org/10.37934/araset.53.1.7385

• Journal Article Type: Article
• Acceptance Date: Aug 21, 2024
• Online Publication Date: Oct 3, 2024
• Publication Date: 2025
• Deposit Date: Oct 10, 2024
• Publicly Available Date: Oct 10, 2024
• Journal: Journal of Advanced Research in Applied Sciences and Engineering Technology
• Electronic ISSN: 2462-1943
• Publisher: Semarak Ilmu Publishing
• Peer Reviewed: Peer Reviewed
• Volume: 53
• Issue: 1
• Pages: 73-85
• DOI: https://doi.org/10.37934/araset.53.1.7385
• Keywords: Electrical tree, Image de-noising, Image segmentation, Median, Noise, Otsu thresholding, TWWF, Wiener