Some edge detection algorithms based on spatial and wavelet technology can detect image edge of limited direction effectively. Since these algorithms haven't fully utilized field information, there would be great error around the complex edge area in the detection results. To solve such kind of problem, a novel edge detection algorithm by combining nonsub- sampled contourlet transform (NSCT) and Canny algorithm is proposed in this paper. Simulation results are displayed to prove that this algorithm can extract more image edge details than Canny algorithm and it also has good continuity and robustness.
An enhanced filtering method in Contourlet transform domain is proposed in this paper. According to local properties, SAR image will be firstly divided into homogeneous area, non-homogeneous area and edge area. Then average filtering method is applied to the homogeneous area, Contourlet transform de-noising method applied to the non-homogeneous area and edge area retained directly. It's proved that not only can we effectively eliminate the noise but also maintain edge details through this method. Compared with other classical filters, the capability to keep the edge details is stronger.