Quality Assessment And Target Recognition In SAR Images

SAR plays an important role in military reconnaissance and civil activity, and SAR images are more and more widely used. Then it is of practical significance and broad prospect to carry out the research on SAR image application. However, due to the special nature of SAR images, there are some characteristic quality issues in SAR images, which make its interpretation more difficult and affect its application ultimately. Therefore, research on SAR image quality assessment and its application is of great significance.In this paper the features of the SAR imaging are studied first, and the characteristics of SAR images are analyzed from the standpoint of the geometry, radiation, statistical distribution and so on. Then from the perspective of image acquisition, five objective parameters are selected to do quality assessment on SAR images, including the mean, variance, equivalent number of looks, radiometric resolution and grayscale resolution. It is verified by experiments on the real SAR image database that the initial quality assessment of SAR images using these five parameters is efficient and intuitive. From the perspective of image content, for SAR images with the gain problem, a gain-detecting algorithm is proposed based on the normalized row/column mean, which can detect effectively ones with the gain problem from SAR images and mark the location of the gain changes on these images. This can help to give suggestions on the improvements in SAR systems.An unsupervised segmentation algorithm for high-resolution SAR images is proposed based on homogeneity criterion. According to the characteristics of SAR images, a novel homogeneity criterion based on JSEG (J-Segmentation) was proposed to reduce the impact of speckle noise on the segmentation. After preprocessing, a gray class-map is created. Using the homogeneity criterion, the gray class-map is mapped to a new data which can indicate where are region centers and where are region boundaries. In the new map, low and high values correspond to possible region centers and region boundaries. According to this feature, the new map is segmented with region growing. The performance of the approach is verified that the algorithm is more accurate in line with a visual interpretation especially for those SAR images with relatively weak targets, and this algorithm is fast, efficient and beneficial for practical application and it has lower computational complexity. A novel SAR image segmentation algorithm based on Local Median Fitting C-V model (LMFCV-SIS) is proposed according to the characteristics of SAR images. The main idea of the algorithm is that the LMF of the pixel and its neighbors is used to form an energy and the final evolution of the curve is given by the minimization of the energy. The performance of the approach is verified by plenty of real airborne SAR images and the experimental results on the real data show its efficiency and accuracy.Finally, an authentication system is established for quality assessment and target recognition of SAR images. Using the authentication system the quality of SAR images can be assessed from different angles, including objective assessment, gain detection, ghost detection, blur extent evaluation and so on. The system can also be used for doing a variety of applications, including road recognition, river recognition, bridge recognition and so on. In this system, a large number of experiments are carried out on SAR images in the database. Using the comprehensive analysis of the results of quality assessment and those applications, SAR images can be well understood, and the basis can be given for the development and improvement of SAR systems and SAR data acquisition.