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Extraction of Satellite Image using Particle Swarm Optimization
Harish Kundra, V.K.Panchal, Sagar Arora, Karandeep Singh, Himashu Kaura, Jaspreet Singh Phool
Pages - 86 - 92 | Revised - 25-02-2010 | Published - 08-04-2010
Published in International Journal of Engineering (IJE)
MORE INFORMATION
KEYWORDS
Objects extraction, Google Earth image, Unsupervised Learning PSO algorithm
ABSTRACT
Of all tasks in photogrammetry the extraction of cartographic features is the most time consuming. Fully automatic acquisition of features like roads and buildings, however, appears to be very difficult. The extraction of cartographic features form digital satellite imagery requires interpretation of this imagery. The knowledge one needs about the topographic objects and their appearances in satellite images in order to recognize these objects and extract the relevant object outlines is difficult to model and to implement in computer algorithms. This paper introduces Particle Swarm Optimization based method of object extraction from Google Earth image (satellite image). This paper deals with the land cover mapping by using swarm computing techniques. The motivation of this paper is to explore the improved swarm computing algorithms for the satellite image object extraction.
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Associate Professor Harish Kundra
Rayat institute of Engineering & IT - India
Dr. V.K.Panchal
- India
Dr. Sagar Arora
- India
Dr. Karandeep Singh
- India
Dr. Himashu Kaura
- India
Associate Professor Jaspreet Singh Phool
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