Study On The Images Fusion ,Mosaic And Map Based On The Remote Sensed Image With High Spatial Resolution And Multi-sources

The mosaic of satellite remote sensing image means that two or multiple images are jointed into one wider image, in order to meet the application of remote sensing images in various fields.In the actual research and application, remote sensing images acquired from different satellite sensor and different season usually have to be joined up. As the parameters of different sensor and satellite image are inconsistent, combined with different acquisition date and system processing which result differences of the geometric distortion and radiation, the brightness values of same feature in adjacent images are inconsistent. Therefore, remote sensing images from different sources must be solved registration and color equalization to make the hue after image mosaicing approximately identical. The study based on the research achievements of predecessors and study myself mainly discusses the mosaic and color equalization approach of merging high resolution remote sensing images form different sources.The study depends on the remote sensing image processing software ERDAS IMAGINE v9.2 and ARC Info as technology platform, selects Ulan Buh desert as study area, and uses high-resolution remote sensing images from SPOT5 and ALOS as data source. The study based on preprocessing, registration,,and the color equalization approach learning from their predecessors and a series of processing reach aims that color equalization, automatic mosaic, mapping. It laid a foundation for the following work.The content and the results of this study are as follows:(1) Using 1:5 million map to realize the geometric correction of remote desert region by collecting a large number of ground control points, the results show that using this method to correct high-resolution remote sensing images is feasible.(2) Through band matching and geometric correction of multi-source remote sensing images to ensure the quality of the mosaic and to achieve multi-source remote sensing images consistency of spatial resolution.(3) Data of multiple sources are balanced in color process to meet the mapping needs.