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

被引:0
|
作者
Chikohora, Edmore [1 ]
Esiefarienrhe, Bokuhwo M. [2 ]
Chikohora, Teressa T. [3 ]
机构
[1] Namibia Univ Scie & Technol, Windhoek, Namibia
[2] North West Univ, Mafikeng, South Africa
[3] Botho Univ, Francistown, Botswana
关键词
Feature extraction; Parameterization; Dimensionality reduction; Big Oh notation; Fitness value; Growth rate function;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:165 / 169
页数:5
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