A hybrid and hierarchical approach to aerial image registration
Abbreviated Journal Title
Int. J. Pattern Recognit. Artif. Intell.
image registration; optical flow; phase correlation; Gaussian/Laplacian; pyramid; INVARIANT MOMENTS; ALGORITHM; Computer Science, Artificial Intelligence
This paper proposes a hybrid approach to image registration for inferring the a. ne transformation that best matches a pair of partially overlapping aerial images. The image registration is formulated as a two-stage hybrid approach combining both phase correlation method (PCME) and optical flow equation (OFE) based estimation algorithm in a coarse-to-fine manner. With PCME applied at the highest level of decomposition, the initial a. ne parameter model could be first estimated. Subsequently, the OFE-based estimation algorithm is incorporated into the proposed hybrid approach using a multi-resolution mechanism. PCME is characterized by its insensitivity to large geometric transform between images, which can effectively guide the OFE-based registration. For image pairs under salient brightness variations, we propose a nonlinear image representation that emphasizes common intensity information, suppresses the non-common information between an image pair, and is suitable for the proposed coarse-to-fine hierarchical iterative processing. Experimental results demonstrate the accuracy and efficiency of our proposed approach using different types of aerial images.
International Journal of Pattern Recognition and Artificial Intelligence
"A hybrid and hierarchical approach to aerial image registration" (2007). Faculty Bibliography 2000s. 7809.