Title :
High quality DEM generation from PCIAS
Author :
Yan, Hongshi ; Liu, Jian-Guo ; Morgan, Gareth ; Liu, Cheng-Chien
Author_Institution :
Dept. of Earth Sci. & Eng., Imperial Coll. London, London, UK
Abstract :
This paper presents an efficient Phase Correlation based Image Analysis System (PCIAS) for high quality DEM generation. A multi-resolution phase correlation based disparity estimation and refinement algorithm has been implemented in PCIAS. It can easily cope with the precise disparity estimation from sub-pixel to very large disparity range with varying baseline/distance ratio in vertical or slightly oblique view stereo imaging. The PCIAS is now a fully operational, professional C++ software package equipped with a robust phase correlation engine, which is among the most advanced technology for sub-pixel image feature shift analysis, and is able to achieve <;1/50th pixel accuracy in dense disparity map estimation. Our experiment indicates PCIAS can generate high quality DEM from very narrow baseline satellite image pairs with view angle difference as small as just 1 degree.
Keywords :
cartography; correlation methods; digital elevation models; geophysical signal processing; image resolution; phase estimation; remote sensing; stereo image processing; PCIAS; baseline-distance ratio; dense disparity map estimation; digital elevation models; high quality DEM generation; multiresolution phase correlation; narrow baseline satellite image pairs; oblique view stereo imaging; phase correlation based image analysis system; professional C++ software package; refinement algorithm; robust phase correlation engine; subpixel image feature shift analysis; Accuracy; Correlation; Estimation; Fitting; Image color analysis; Robustness; Satellites; DEM generation; PCIAS; disparity estimation; phase correlation; sub-pixel;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6352501