BBO Comparison with other Nature Inspired Algorithms to Resolve Mixels  

Abstract

Remote sensing is defined as a technique for acquiring the information about an object without making physical contact with that image via remote sensors. But the major problem of remotely sensed images is mixed pixel which always degrades the image quality. In this paper we attempted to present an approach for resolving the mixed pixels by using optimization/ Evolutionary algorithm i.e. Biogeography based optimization. EA’s are the most well known algorithms among nature inspired algorithms, which is based on the biological evolution in nature that is being responsible for the design of all living beings on earth. A family of successful EAs comprises genetic algorithm (GA), genetic programming (GP), Differential Evolution, evolutionary strategy (ES) , Artificial Bee Colony Algorithm (ABC), Particle swarm optimization (PSO), Ant Colony Optimization (ACO). This paper also deals with the comparison of BBO and others EA’s so that we can proof BBO as best algorithm for resolving MIXELS problem. 

Authors and Affiliations

Mittu Mittal , Gagandeep Kaur

Keywords

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  • EP ID EP151696
  • DOI -
  • Views 77
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How To Cite

Mittu Mittal, Gagandeep Kaur (2013). BBO Comparison with other Nature Inspired Algorithms to Resolve Mixels  . International Journal of Advanced Research in Computer Engineering & Technology(IJARCET), 2(6), 2114-2118. https://europub.co.uk/articles/-A-151696