Title :
Measures for an Objective Evaluation of the Geometric Correction Process Quality
Author :
Gonçalves, Hernâni ; Gonçalves, José A. ; Corte-Real, Luís
Author_Institution :
Dept. de Mat. Aplic., Univ. do Porto, Porto
fDate :
4/1/2009 12:00:00 AM
Abstract :
The geometric correction process is a crucial step in remote sensing applications. This process is frequently manually performed-which is a laborious task in many situations-as automatic image registration methods are still far from being broadly applied. One of the reasons that justify the absence of a broad application of automatic image registration methods is the lack of measures for an objective and automated analysis of the image registration process quality. The root mean square (RMS) of the residuals is the only quantitative evaluation which is generally used in this process, with the final validation of the geometric correction process being a qualitative analysis. Therefore, in both ldquohumanrdquo and automatic image registration processes, an objective evaluation of its quality is required. In this letter, we propose several measures for an objective evaluation of the geometric correction process, as a complement to the traditional RMS of the residuals and visual inspection. Two scenarios of control point distribution and the most common residual distributions were considered. With the proposed measures, we intend to cover the most common qualitative analysis aspects. This has particular importance under the scope of automatic image registration methods, where an automatic evaluation of the results is also required.
Keywords :
geophysical signal processing; image registration; numerical analysis; remote sensing; automated process quality analysis; automatic image registration methods; control point distribution; geometric correction process quality; image registration process quality analysis; objective evaluation measures; objective process quality analysis; remote sensing; residual root mean square; Ground control points (CPs); image registration; quality assessment; remote sensing;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2008.2012441