Automatic Georeferencing of Airborne Pushbroom Scanner Images With Missing Ancillary Data Using Mutual Information

Abstract

We describe a methodology that is used for the automatic georeferencing of multispectral images acquired from airborne pushbroom imaging cameras. This methodology is based upon the dense registration of flight strips data onto a reference orthoimage and uses the mutual information criterion to make the raw (source) image and the orthoimage (target) aligned. By taking into account a rigorous modeling of the pushbroom imaging process, we show how the mutual information between the raw image and the orthoimage can be used to estimate unknown or inaccurate flight attitude parameters [(tilt bias angles, instantaneous yaw, and height above ground level (AGL)] without using any ground control nor tie points. Moreover, we show how a coarse digital elevation model can be incorporated in the proposed procedure to improve the geocorrection and even estimate a digital surface model of the surveyed area. Two experiments using Compact Airborne Spectrographic Imager (CASI) and Airborne Imaging Spectroradiometer for Applications (AISA) Eagle sensor data are described and show the effectiveness of our approach, with planimetric root mean square errors being in the range of two to four pixels, depending on the flatness and land cover, and altimetric root mean square errors being less than 1% of the flight altitude AGL.