Technical Program

Paper Detail

Paper:	IMDSP-P12.7
Session:	Feature Extraction and Analysis
Time:	Thursday, May 18, 16:30 - 18:30
Presentation:	Poster
Topic:	Image and Multidimensional Signal Processing: Feature Extraction and Analysis
Title:	HIERARCHICAL REGION-BASED IMAGE REGISTRATION IN SCALE SPACE
Authors:	Nan Jiang, Jennie Si, Arizona State University, United States; Glen P. Abousleman, General Dynamics C4 Systems, United States
Abstract:	This paper presents a new method for image registration for real natural scenes. The method is based on the observation that most natural scenes are actually 3-D. If the assumption of weak perspective is violated, the error in image registration induced by parallax is increased, leading artifacts or blurs in image mosaic. Our method first applies the affine-invariant point detector in scale space. After clustering feature point pairs, an initial global transformation is formed based on majority correspondence. The global transformation is evaluated in each region at certain scale determined by inliers. The global model is optimized for local registration by minimizing Least Square Error. This method is more robust than standard image registration algorithms on images subject to un-calibrated camera motion.