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A unified approach to the geometric rectification of remotely sensed imagery

University of British Columbia

Many applications of remotely sensed digital imagery require images that are corrected for geometric distortions. It is often desirable to rectify different types of satellite imagery to a common data base. A high throughput rectification system is required for commercial application. High geometric and radiometric precision must be maintained. The thesis has accomplished the following tasks: 1. The sensors used to obtain remotely sensed imagery have been investigated and the associated geometric distortions inherent with each sensor are identified. 2. The transformation between image coordinates and datum coordinates has been determined and the values of the parameters in the transformation are estimated. 3. A unified rectification approach has been developed, for all types of remotely sensed digital imagery, which yields a high system throughput. 4. Use of digital terrain models in the rectification process to correct for relief displacement has been incorporated. 5. An efficient image interpolation algorithm has been developed. This algorithm takes into account the fact that imagery does not always correspond to sampling on a uniform grid. 6. The applications of rectified imagery such as mosaicking and multisensor integration have been studied. 7. Extension of the rectification algorithm to a future planetary mission has been investigated. The sensors studied include TIROS-N, Landsat-1, -2 and -3 multispectral scanners, Seasat synthetic aperture radar, Landsat-4 thematic mapper and SPOT linear array detectors. Imagery from the last two sensors is simulated.

Text

2010-06-14

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http://hdl.handle.net/2429/25697

Computer Science

University of British Columbia

Graduate