An automatic accuracy evaluation approach of band registration for multi-spectral imagery

Considering band misalignment caused by attitude jittering or other factors, band registration becomes the most critical pre-processing step for multispectral imagery as the registration result will directly influence the following applications. So band registration accuracy evaluation is necessary before registered imagery going through the next processing step. This paper proposes an automatic approach to evaluate the band registration accuracy for multi-spectral imagery. The proposed method is based on the theory of image matching, which includes three main steps: 1) feature points detection, and then 2) corresponding points matching, and 3) accuracy evaluation. Experiments are designed for the validation of the proposed approach with RGB image of Toronto in Canada captured by the Microsoft Vexcel's UltraCam-D (UCD) camera, in which quantitative analyses are applied to assess the accuracy and reliability of the method. And evaluation result for multi-spectral images of satellite, i.e., ZiYuan-3, by this method were presented. The result shows that the proposed method can automatic evaluate band registration accuracy for multi-spectral imagery accurately, efficiently and objectively.