Analysis and Performance Evaluation of Parameterization Algorithms in Remote Sensing Image Processing

Abstract

The study reviews currently used Feature Extraction Techniques (FET) and analyze their parameterization strategies as discussed by different authors, thereby setting the ground to do a performance evaluation of the GenApp, a novel adaptive algorithm for parameterization of FET that was introduced in our previous publication. We performed efficiency analysis, worst-case analysis and fitness value tests to the feature extraction algorithms to evaluate their strengths in a comparative manner. The results obtained from the experiments reflect a marginally higher complexity value on the execution of the GenApp, a reduced number of generations in finding an optimum parameter value and a relatively constant fitness value which gives us confidence in the algorithm's potential to improve parameterization and output images from FET.