scholarly journals Feature Extraction from High-Resolution Remotely Sensed Imagery using Evolutionary Computation

10.5772/15915 ◽  
2011 ◽  
Author(s):  
Henrique Momm ◽  
Greg Easso
Keyword(s):  
Feature Extraction ◽  
High Resolution ◽  
Evolutionary Computation ◽  
Remotely Sensed ◽  
Remotely Sensed Imagery

scholarly journals Exploration of Genetic Programming Optimal Parameters for Feature Extraction from Remote Sensed Imagery

2014 ◽  
Vol XL-1 ◽  
pp. 113-120
Author(s):  
P. Gao ◽  
S. Shetty ◽  
H. G. Momm
Keyword(s):  
Feature Extraction ◽  
Genetic Programming ◽  
Evolutionary Computation ◽  
Evolutionary Process ◽  
Remotely Sensed ◽  
Computational Time ◽  
Remotely Sensed Imagery ◽  
Optimal Input ◽  
Fitness Value ◽  
Input Parameters

Evolutionary computation is used for improved information extraction from high-resolution satellite imagery. The utilization of evolutionary computation is based on stochastic selection of input parameters often defined in a trial-and-error approach. However, exploration of optimal input parameters can yield improved candidate solutions while requiring reduced computation resources. In this study, the design and implementation of a system that investigates the optimal input parameters was researched in the problem of feature extraction from remotely sensed imagery. The two primary assessment criteria were the highest fitness value and the overall computational time. The parameters explored include the population size and the percentage and order of mutation and crossover. The proposed system has two major subsystems; (i) data preparation: the generation of random candidate solutions; and (ii) data processing: evolutionary process based on genetic programming, which is used to spectrally distinguish the features of interest from the remaining image background of remote sensed imagery. The results demonstrate that the optimal generation number is around 1500, the optimal percentage of mutation and crossover ranges from 35% to 40% and 5% to 0%, respectively. Based on our findings the sequence that yielded better results was mutation over crossover. These findings are conducive to improving the efficacy of utilizing genetic programming for feature extraction from remotely sensed imagery.

scholarly journals SUPPORT OF MULTISPECTRAL VERY HIGH RESOLUTION REMOTELY SENSED IMAGERY FOR OLD-GROWTH BEECH FOREST DETECTION

2010 ◽  
pp. 519-527 ◽  
Author(s):  
Silvia Di Paolo ◽  
Diego Giuliarelli ◽  
Barbara Ferrari ◽  
Anna Barbati ◽  
Piermaria Corona
Keyword(s):  
High Resolution ◽  
Remotely Sensed ◽  
Beech Forest ◽  
Old Growth ◽  
Remotely Sensed Imagery ◽  
Very High

A semi-automatic segmentation procedure for feature extraction in remotely sensed imagery

2005 ◽  
Vol 31 (3) ◽  
pp. 289-296 ◽  
Author(s):  
Quanfa Zhang ◽  
Goran Pavlic ◽  
Wenjun Chen ◽  
Robert Fraser ◽  
Sylvain Leblanc ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Automatic Segmentation ◽  
Remotely Sensed ◽  
Remotely Sensed Imagery

Use of Remotely Sensed Imagery in Cyber Warfare and Cyber Counterterrorism

2011 ◽  
pp. 298-305
Author(s):  
Gang Gong ◽  
Mark R. Leipnik
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remotely Sensed ◽  
Aerial Photographs ◽  
The Internet ◽  
Cyber Warfare ◽  
Future Trends ◽  
Remotely Sensed Imagery ◽  
General Terms ◽  
High Resolution Imagery

Remote sensing refers to the acquisition of information at a distance. More specifically, it has come to mean using aerial photographs or sensors on satellites to gather data about features on the surface of the earth. In this article, remote sensing and related concepts are defined and the methods used in gathering and processing remotely sensed imagery are discussed. The evolution of remote sensing, generic applications and major sources of remotely sensed imagery and programs used in processing and analyzing remotely sensed imagery are presented. Then the application of remote sensing in warfare and counterterrorism is discussed in general terms with a number of specific examples of successes and failures in this particular area. Next, the potential for misuse of the increasing amount of high resolution imagery available over the Internet is discussed along with prudent countermeasures to potential abuses of this data. Finally, future trends with respect to this rapidly evolving technology are included.

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