Optimizing dual energy X-ray image enhancement using a novel hybrid fusion method

Airport security is still a main concern for assuring passenger safety and stopping illegal activity. Dual-energy X-ray Imaging (DEXI) is one of the most important technologies for detecting hidden items in passenger luggage. However, noise in DEXI images, arising from various sources such as electr...

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Veröffentlicht in:Journal of X-ray science and technology Jg. 32; H. 6; S. 1553
Hauptverfasser: Fahad, Muhammad, Zhang, Tao, Khan, Sajid Ullah, Albanyan, Abdullah, Siddiqui, Fazeela, Iqbal, Yasir, Zhao, Xin, Geng, Yanzhang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 23.12.2024
Schlagworte:
Airports
Algorithms
Humans
Image Processing, Computer-Assisted - methods
Radiographic Image Enhancement - methods
Security Measures
Signal-To-Noise Ratio
Wavelet Analysis
X-Rays
background noise
Discrete wavelet transform
dual energy X-ray imaging
image fusion
Poisson noise
stationary wavelet transform
ISSN:1095-9114, 1095-9114
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Zusammenfassung:Airport security is still a main concern for assuring passenger safety and stopping illegal activity. Dual-energy X-ray Imaging (DEXI) is one of the most important technologies for detecting hidden items in passenger luggage. However, noise in DEXI images, arising from various sources such as electronic interference and fluctuations in X-ray intensity, can compromise the effectiveness of object identification. To address the challenge of noise interference in DEXI, this study aims to develop and validate a robust denoising technique using the Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT). The proposed method targets and removes background and Poisson noise in DEXI images, improving object recognition accuracy. During the denoising process, images are decomposed into several subbands, and thresholding techniques are applied to minimize noise while preserving important information. The images are then reconstructed to provide a cleaner and more accurate depiction of scanned objects. Experimental results demonstrate the effectiveness of the DWT and SWT-based denoising strategy in preserving critical data while suppressing noise in DEXI. The performance of the denoising technique is quantified using Peak Signal-to-Noise Ratio (PSNR) and Mean Squared Error (MSE). The proposed system achieved an average PSNR of 35.23 and an MSE of 19.52 for 256×256 DEXI images, and an average PSNR of 36.01 and an MSE of 16.29 for 512×512 DEXI images. The results highlight the achievement of the proposed approach in enhancing the quality of DEXI for improved security screening, demonstrating its potential application in airport security systems.
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ISSN:1095-9114
1095-9114
DOI:10.3233/XST-240227