A Novel Image Registration Algorithm for Remote Sensing Under Affine Transformation

With the help of the histogram of triangle area representation (TAR) and feature matching strategy, a new effective image registration approach for remote sensing is proposed in this paper. This approach is based on a robust transformation parameter estimation algorithm called the histogram of TAR sample consensus (HTSC in short). The HTSC algorithm can replace the existing random sample consensus (RANSAC) and progressive sample consensus (PROSAC) methods that have been widely used in the transformation parameter estimation step of remote-sensing image registration, for it can efficiently calculate the consensus set with a higher accuracy. This paper lays down a new way to build a robust transformation parameter estimator based on the invariance constraint for remote-sensing image registration. Analogous to the two types of well-known existing transformation parameter estimation methods RANSAC and PROSAC, HTSC can serve as a new type (or the third type if we treat RANSAC and PROSAC as the first and the second types) of such methods, as it adopts the transformation-invariance information to find the consensus.