A Genetic Approach to Parameterization of Feature Extraction Algorithms in Remote Sensing Images
Edmore Chikohora1, Obeten O. Ekabua2
1Edmore Chikohora, Department of Computer Science North-West University, Mafikeng Campus, Mmabatho, South Africa.
2Obeten O. Ekabua, Department of Computer Science North-West University, Mafikeng Campus, Mmabatho, South Africa.
Manuscript received on April 26, 2014. | Revised Manuscript received on May 03, 2014. | Manuscript published on May 05, 2014. | PP: 144-149 | Volume-4 Issue-2, May 2014. | Retrieval Number: B2234054214/2014©BEIESP
Open Access | Ethics and Policies | Cite
©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: Genetic Algorithms (GA) are an adaptive heuristic search algorithm found on the evolutionary ideas of natural selection. In this paper, we propose an adaptive heuristic based on the Gabor Filter (GF) to generate useful solutions to optimization of parameter selection strategies for Feature Extraction Algorithms (FEA) in Remote Sensing Images. Experiments were done using computer simulations and a critical analysis on performance of the heuristic algorithm is done in a comparative manner with the rest of the algorithms.
Keywords: Average Ranking, Square Error, Local Extrema, Phenotype, Genotype.