Change Detection Of Satellite Imagery Considering Projection Difference

With the increase of production and development of society in this years, especially the construction of city is more highlighted .In order to learn from the layout of city , the utility of land ,illegal buildings, the conditions of vegetation covers and layout of road so on, it is necessary to monitor the change of city. With the help of RS, the method of detecting the urban change by RS images is more and more popular.But the traditional RS images have a shortcoming: low resolution, so they can not be used for precise change detection (such as the change detection of road and house etc.).In fact, the high resolution satellite images can reflect the detail of change, which is fit for detection of city change. Apparently, high resolution satellite images will make a important pole in detection of city change.Generally, the precision of registering makes direct effect on the result of detection, especially for high resolution satellite images. On the one hand, because of misregistration in local regions, the error resulted from projection may be regarded as change. On the other hand, the buildings which cause the error of projection, always give rise to shade, then lead to the change of local gray. So during the process of detection by high resolution satellite images, the effect of projection and shade must be taken into accounted.In this paper, by use of high resolution satellite images at different points of time, based on the traditional method, take projection and shade into the effect of change detection. The main contents as follows:1. analyze the law of RS image change, and summary the traditional detection method.2. Implement the detection of method by image regression, and the experiments which covers various timely images of airplane prove its superiority.3. Exploiting the texture difference method on the detection of high resolution RS images, and make some experiments and analysis.4. Put forward to the method to decrease the effect resulted from shade. Firstly, apply the traditional detection method, then extract the shade by producing binary images, furthermore compare the changed regions resulted from shade with the shape difference in shade images, and select the similar shade images in shape for eliminate the effect of shade.5. Put forward to two methods for reducing the effect of projection difference. The first method is based on shift change frequency. On the base of traditional detection effect, translate all the pixels changed, and get the various images. By the detecting the shifted images and origin images, get the various change images. Then by deducing the effect resulted from translation, find the direction of projection difference offset. In the direction we can reduce effect of projection difference .The second method is based on region change frequency. Firstly segment the images ,then according to the preliminary result ,make a statistics on the change frequency of various regions for determining whether there are some change.