An Edge Detection Approach Based on Statistical Signal Processing and B-Spline Wavelet for Millimeter Wave Images
基于统计处理和B样条小波变换的毫米波图像边缘检测

This paper proposes an edge detection scheme for millimeter wave images, which has low resolution and large noise. It introduces standard gradient strength according to statistical signal processing theory. The basic idea is to employ cubic B-spline as edge detector. The wavelet transform results reflect the variations for images--along horizontal edges and vertical edges, which are used with statistical information together to get the standard gradient magnitude. For each millimeter wave image a fixed and identical threshold is adopted to detect the image edges roughly. Finally, non-maximum suppression phase and a filter are introduced to get the specific edges. The experiment results demonstrate that the scheme is effective and feasible for detecting the edge of the hidden objects on the background of the human body, which meet the real time requirement in custom.