A Coarse Elevation Map-based Registration Method for Super-resolution of Three-line Scanner Images

Three-line scanner imagery provides three overlapped images in an along-base direction, and creates a possible avenue to obtain higher quality images through the application of the super-resolution. Accurate co-registration of the three images is a key step for super-resolution. However, discontinuities and occlusions resulting from the 3D-to-2D projection cause mis-registration in traditional 2D-image-level co-registration methods. In this paper, we address this problem by introducing 3D information extracted from image triplets by using GPS/IMU data as an approximation. The core of the proposed method is to use a number of height layers derived from feature points and image partitions, in the form of a coarse elevation map (CEM), as a 3D constraint to restrict registration on the corresponding height. In terms of super-resolution, we also propose a tree-based fast adaptive template matching method for Knife-edge detection to fully automate the SRKE super-resolution algorithm. Experimental results show that the proposed method produces improved registered images and accordingly yields signifi cant resolution enhancement as compared to other methods.