Modelling th# push broom sensors commonly used in satellite imagery is quite di#cult and computationally intensive due to th# complicated motion ofth# orbiting satellite with respect to th# rotating earth# In addition, th# math#46 tical model is quite complex, involving orbital dynamics, andh#(0k is di#cult to analyze. Inth#A paper, a simplified model of apush broom sensor(th# linear push broom model) is introduced. Ith as th e advantage of computational simplicity wh#A9 atth# same time giving very accurate results compared with th# full orbitingpush broom model. Meth# ds are given for solving th# major standardph# togrammetric problems for th e linear push broom sensor. Simple non-iterative solutions are given for th# following problems : computation of th# model parameters from groundcontrol points; determination of relative model parameters from image correspondences between two images; scene reconstruction given image correspondences and ground-control points. In addition, th# linearpush broom model leads toth#0 retical insigh ts th# t will be approximately valid for th# full model as well.Th# epipolar geometry of linear push broom cameras in investigated and sh own to be totally di#erent from th at of a perspective camera. Neverth eless, a matrix analogous to th e essential matrix of perspective cameras issh own to exist for linear push broom sensors. Fromth#0 it is sh# wn th# t a scene is determined up to an a#ne transformation from two viewswith linearpush broom cameras. Keywords :push broom sensor, satellite image, essential matrixph# togrammetry, camera model The research describ ed in this paper hasb een supportedb y DARPA Contract #MDA97291 -C-0053 1 Real Push broom sensors are commonly used in satellite cameras, notably th# SPOT satellite forth# generatio...

It is known tha ta set of points in 3 dimensions is determined up to projectivity from two views with uncalibrated cameras. It is shown in this paper that this result may be improved by distinguishing between points in front of and behind the camera. Any point tha# lies ina n ima#3 must lie in front of the ca mera producing tha t ima ge. Using thisidea , it is showntha t the scene is determined from two views up toa more restricted cla ss ofma ppings known a# good projecti#:TB1q whicha re precisely those projectivities tha t preserve the convex hull of a# object of interest. An inva#3 a nt of good projectivity known a# the chei# ali# yi set of points is defineda nd it is shown how the cheira lity inva ria ntma y be computed using twounca libra ted views. As demonstra ted theoretica llya nd by experiment the cheira lity inva ria ntma y distinguish between sets of pointstha# a#a projectively equiva#iv t (but not via a good projectivity) . These results lea# to necessa#fi a#e sufficient conditions fora set of corresponding pixels in two ima#25 to be rea# iza# le a# the ima#38 ofa set of points in 3 dimensions. Using simila r methods,a necessa rya nd sufficient condition is given for the the set of points to be determined by two views. If the perspective centres are not separated from the point set by a plane, then the orientation of the set of points is determined from two views. Good projectivities and the cheirality invariant are also defined for point sets in a plane, which allows these new methods to be applied to images of planar objects.