Research On Change Detection Technology Of SAR Image

Remote sensing image change detection is the distinguishing and analyzing process of interested ground object or target changes, the change detection based on SAR image is an important branch of remote sensing image change detection. Around its entire process, this paper involves four parts and research depthly, the main point of the work and innovation are as follows:1.Designed the overall process of change detection based on SAR image, including image filtering, image matching, changes in regional extraction and accuracy evaluation.Also Completed a set of process-oriented change detection system.2.In order to solve the problem of the classical statistical filters relying solely on the window's size of filtering to adjust the filtering capacity in the spatial, I introduce and improve the relevant neighborhood model, descripted a more reasonable of the neighborhood information SAR image in the local filtering window , using the relevant neighborhood model based on improved The MAP filter in suppressing speckle noise at the same time retain a good image of the edge information.3.The problem of constructing differences image in the pixel-level change detection, I improve the method of constructing differences image, using the difference integration ratio make the differences information much richer in the difference image. And then how to obtain the change region from the difference image.This problem can be solved using the Bayes decision theory, at the assumption that the Gaussian distribution, finding the optimal change use non-supervised means,achieving the threshold selection automation. For the traditional threshold method does not take into account differences in image context information, the introduction of the Markov model described in the context of information, effectively reducing the test results in the presence of isolated pixels and improve the change detection accuracy.4.Analysis of the lack of pixel-level change detection and the object-oriented change detection method is proposed, the introduction of Mean Shift Algorithm, Mean Shift algorithm is an effective non-parametric segmentation algorithm, and on the basis of the color gamut-spatial through direclyt estimated feature space probability density function of the local minimum value of the density model to obtain the unknown category, and determine the mode of the unknown, and then make it to the cluster, and this model to the relevant categories,achieving image segmentationThis object-oriented segmentation method to quickly and accurately classified into homogeneous regions. Providing an important basis for change detection in the further.The proposed algorithms are applied to SAR images , and obtained satisfactory experimental results, the reliability and validity are superior to the existing classical algorithm.