Image optimization method for ablation defects in high-voltage cable buffer layers based on X-ray detection technique

This paper proposes an optimization method based on image enhancement and feature detection to address the challenges of low-quality X-ray images,significant noise interference, and difficulty in defect identification during the detection of ablation defects in high-voltage cable buffer layers. By analyzing the advantages of X-ray detection technique and its practical challenges, the study employs a Multi-Scale Retinex with Color Restoration(MSRCR) algorithm to enhance image contrast, balancing dynamic range compression and color constancy, thereby improving the visibility of defects in low-light or lowcontrast regions. The research optimizes the Speeded-Up Robust Features(SURF) detection algorithm by adjusting the Hessian matrix threshold to enhance sensitivity to low-contrast defects. It combines multi-scale analysis with directional constraints to reduce false detections in complex backgrounds and utilizes Lanczos3 interpolation to reconstruct defect edge textures with high fidelity while suppressing ringing artifacts. Practical results demonstrate that this method significantly improves the recognition accuracy and visualization of defect regions in X-ray images, supports automatic localization and magnification, and provides reliable technical support for rapid diagnosis of high-voltage cable buffer layer conditions.