Title :
RSCJ: Robust Sample Consensus Judging Algorithm for Remote Sensing Image Registration
Author :
Li, Bin ; Ye, Hao
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
fDate :
7/1/2012 12:00:00 AM
Abstract :
Problems concerning transformation estimation for remote sensing image registration are studied in this letter. Based on the affine-invariance property of triangle-area representation, a new algorithm called robust sample consensus judging is proposed. It can be embedded into most robust estimation algorithms with hypothesis-and-testing frameworks (such as random sample consensus) and can significantly improve their computational efficiency without sacrificing remote sensing image registration accuracy. Simulation and experimental results show the merits of the proposed algorithm.
Keywords :
estimation theory; image registration; remote sensing; sampling methods; RSCJ; affine-invariance property; computational efficiency; hypothesis-and-testing frameworks; remote sensing image registration; robust estimation algorithms; robust sample consensus judging algorithm; transformation estimation; triangle-area representation; Accuracy; Estimation; Feature extraction; Image registration; Numerical simulation; Remote sensing; Robustness; Image registration; remote sensing; robust estimation;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2011.2175434