An X-Ray Image Enhancement Algorithm for Dangerous Goods in Airport Security Inspection

Abstract

This paper presents an X-ray image enhancement algorithm specifically designed for airport security inspection of dangerous goods. The proposed algorithm employs a multi-step process to enhance the quality and visibility of X-ray images, aiding security personnel in accurately identifying potential threats. The first step of the algorithm involves Contrast Limited Adaptive Histogram Equalization (CLAHE) enhancement. Grayscale images are calculated for each of the color channels (R, G, and B) independently, and then merged to create an enhanced grayscale image, which effectively improves the image's contrast and enhances the overall visibility of objects. Subsequently, the algorithm utilizes an improved Unsharp Mask (USM) technique for sharpening the CLAHE-enhanced image. The USM algorithm accentuates details such as image edges and shapes, further enhancing the clarity of objects within the X-ray scan. To achieve a refined and optimal image fusion, the USM-sharpened image is combined with the original image using a superposition coefficient at the second level. Finally, the proposed algorithm performs image fusion by applying appropriate weights to the original image and the USM-sharpened image. This step aims to minimize image color distortion and deliver a visually coherent and informative output. The effectiveness of the proposed X-ray image enhancement algorithm is demonstrated through experimental evaluation and comparison with existing techniques. The results indicate that the algorithm significantly improves the quality of X-ray images, providing airport security personnel with enhanced capabilities for accurate and reliable identification of dangerous goods during security inspections.