Feasibility assessment of multiple sensor data fusion

With the improvements of remote sensing sensors, the quality and quantity of remote sensing data is also increased. Data from different sensors has different properties, therefore, it is an important issue to fuse data together. Most of remote sensing data can be classified into two categories, image and point cloud. Both digital optical and radar images are raster data, which can be stored in matrix forms. The row number, column number, band number and polarization are all integers. On the other hand, point cloud from lidar are points in three dimensional space. They contains longitude, latitude and height, which are usually not integers. There are also methods to convert point cloud into matrix, but some information will be lost and also cause some error. In this project, we will conduct comparison with published methods in literature and analyze their advantages and disadvantages. Finally, we will try to propose fusion method for various of applications.