A Contrast Enhancement Approach for Improving Analysis in X-Ray Container Scan Images

X-ray container imaging systems generate monochromatic images that are primarily used for the detection of prohibited items associated with smuggling activities. Within the scope of this study, two image enhancement algorithms were developed to reveal concealed or subtle details within scan images. For the purpose of noise reduction, median filtering and sharpening filters were utilized in the respective algorithms. In the contrast enhancement stage, one algorithm employed Histogram Equalization, while the other utilized Contrast Limited Adaptive Histogram Equalization (CLAHE). In the CLAHE-based method, optimal parameters were determined based on the entropy of the image, particularly by tuning the block size and clipping limit to achieve ideal enhancement results. To mitigate the naturally occurring airborne noise frequently observed in X-ray scans, contrast adjustment was further refined based on the median brightness of the image, which contributed to preserving a more natural visual appearance. The effectiveness of the developed algorithms was evaluated using objective image quality metrics, including Signal-to-Noise Ratio (SNR) and entropy. Results indicate that contrast-enhanced images improve the distinguishability of objects with similar intensity levels, thereby assisting X-ray operators in anomaly detection and interpretation during inspection processes.