The Use of Principal Components for Creating Improved Imagery for Geometric Control Point Selection

A directed principal component (PC) analysis and its transformation was applied to 7-channel thematic mapper simulator (TMS) data and 4-channel LANDSAT multispectral scanner system (MSS) data collected over the city of Lancaster, Pennsylvania, to create improved imagery for geometric control point selection for image to image registration. Nineteen temporally stable geometric control points, such as road interactions and bridges, were selected for a 236 sq km area. The control points were visible on both the TMS and MSS imagery. On the first attempt the corresponding image control points were selected on both data sets without using the principal components transformation. Many of the road intersection locations were visible but the actual road crossings could not be distinguished. As a result, mensuration errors using raw data exceeded the equivalent of two (79 x 79 m) pixels. The application of a guided principal components transformation yielded TMS and MSS single band images showing improved detail in the scene's urban and residential infrastructure. The PC transformed data sets were then utilized for the reselection of geometric control points. By shown greater detail, control points on both the TMS and MSS imagery could be located with greater precision using the PC transformed data.