Simultaneous super-resolution reconstruction based on plane array staring remote sensing images

A group of images for one scene can be obtained by plane array staring remote sensing system. So researchers often use multi-frame image super-resolution reconstruction to produce images with higher spatial resolution. However, most of reports regard super-resolution reconstruction as an isolated part ignoring that geometric parameters of imaging system have the ability to optimize the reconstruction model. Therefore, the influence of attitude angle on resolution changes in different directions was analyzed particularly. Meanwhile, the corresponding anisotropic blur estimation was presented to improve the accuracy of discrimination model. Because of the matching parameter as a significant role in super-resolution reconstruction, for improving the accuracy of the matching parameter estimation and decreasing the global initial matching error caused by the system, the algorithm of simultaneously optimizing super-resolution image and matching parameters based on maximum a posteriori estimation was proposed. This method takes advantage of the useful information of imaging system and improve the robustness of matching parameter by synchronous optimizing. The experimental results demonstrate that the method of our paper is better than existed algorithms in detail information and definition observing by eyes. In addition, the mean square error was reduced 0.3 times, and the information entropy was increased 1.2 in average.