Edge detection for millimeter-wave images based on curvelet transform

The millimeter-wave images have low resolution and heavy noise. Hence it is hard to detect the edges in such images. A detection scheme based on curvelet transform is proposed. The idea is to suppress noise through Wrapping algorithm of curvelet transform at first, then determine gradient amplitude of pixels. At last the non-maximum and double threshold method are used to obtain the edges. The experiments show that clear edges of human and object images in millimeter-wave images can be detected efficiently, and the scheme implements fast.