遥感图像处理中的参数化算法分析与性能评价

Edmore Chikohora, B. M. Esiefarienrhe, T. Chikohora
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引用次数: 0

摘要

该研究回顾了当前使用的特征提取技术(FET),并分析了不同作者讨论的参数化策略,从而为GenApp的性能评估奠定了基础,GenApp是我们之前发表的一种用于FET参数化的新型自适应算法。我们对特征提取算法进行了效率分析、最坏情况分析和适应度值测试,以比较的方式评估它们的优势。实验结果表明,GenApp执行的复杂度值略高,寻找最佳参数值的代数减少,适应度值相对恒定,这使我们相信该算法有可能改善参数化和FET输出图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and Performance Evaluation of Parameterization Algorithms in Remote Sensing Image Processing
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.
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