Research On SAR Image Matching Technology Based On Feature

Image matching is one of the key techniques for such application as the fusion of remote sensing images, technology in automatic aircraft navigation and so on. Optics image acquisition can be easily influenced by lighting, weather and the alternation of day and night, while Synthetic Aperture Radar(SAR) can work all-weather and day-or-night. without being influenced. Therefore, SAR image matching turns out to be the direction, at the same time, the difficulty of matching technique. In view of such characteristics as low S/N ratio and great image distortion of SAR, this thesis makes respective study on same-source SAR image matching and the matching of SAR image with optics image.Contents and innovations:1. This article makes a brief introduction of the principle and characteristics of SAR image, and according to these characteristics, studies the stages and general methods of SAR image matching.2. This article elaborates the preprocessing of SAR image. That is, decreasing the speckle noise of SAR image by wavelet transform with a thresholding, which receives sound result and is applied to SAR image edge detection.3. To study same-source SAR image matching, the author introduces a method based on Scale Invariant Feature Transform (SIFT) to detect the key-points of SAR image. And as SAR image is different from the ordinary remote sensing image, which features its clearness, the author combines the SIFT feature matching and local gray-scale matching together and puts forward a new controlling method with correlation coefficient for the further elimination of mismatch points. It proves to be very effective to further control the key points with this new method, which resolves the matching problem of same-source SAR images that are distinguished by rotation, scaling and distortion with high precision.4. With regard to the matching of SAR image with optics image, the author establishes an image pyramid with the help of wavelet multi-resolution transform and brings forward a new edge detection method based on improved Canny algorithm. As for the search of edge detection, the author takes breadth-first search so as to overcome the numerous SAR image speckles. Making good use of the detected edge, the author studies the multi-source matching of SAR image with optics image by integrating weighted Hausdorff distance with space distance, which obtains satisfactory results.