Title :
Research on Genetic Algorithm and Ant Colony Optimization Algorithm and Its Application on Multi-CCD Sensor Planing
Author_Institution :
Dept. of Aerial Instrum. & Electr. Eng., First Aeronaut. Inst. of Air Force, Xinyang, China
Abstract :
Based on a deep discussion on the algorithm of multi-CCD sensor planning, genetic algorithm ant algorithm (GAAA) is proposed in this paper. GAAA is superior to ant colony algorithm in time efficiency and also superior to genetic algorithm in solution efficiency. Through optimizing, it improves the resulting efficiency of digital image processing greatly. moreover, it is more convenient to the latter application of digital image dividing, identification, recovering, measuring as well as three-dimensional reconstruction.
Keywords :
CCD image sensors; genetic algorithms; image fusion; image reconstruction; ant colony optimization; digital image dividing; digital image processing; genetic algorithm; multiCCD sensor planing; three-dimensional reconstruction; Algorithm design and analysis; Charge coupled devices; Cities and towns; Encoding; Gallium; Genetic algorithms; Planning; ant algorithm (AA); genetic algorithm (GA); multi-CCD sensor planning;
Conference_Titel :
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9247-3
DOI :
10.1109/GCIS.2010.207
