Welcome to the InfoSci Platform
Reference Hub1
Swarm Intelligence Based on Remote Sensing Image Fusion: Comparison between the Particle Swarm Optimization and the Flower Pollination Algorithm

Swarm Intelligence Based on Remote Sensing Image Fusion: Comparison between the Particle Swarm Optimization and the Flower Pollination Algorithm

Reham Gharbia, Aboul Ella Hassanien
Copyright: © 2017 |Pages: 21
ISBN13: 9781522522294|ISBN10: 1522522298|EISBN13: 9781522522300
DOI: 10.4018/978-1-5225-2229-4.ch023
Cite Chapter Cite Chapter

MLA

Gharbia, Reham, and Aboul Ella Hassanien. "Swarm Intelligence Based on Remote Sensing Image Fusion: Comparison between the Particle Swarm Optimization and the Flower Pollination Algorithm." Handbook of Research on Machine Learning Innovations and Trends, edited by Aboul Ella Hassanien and Tarek Gaber, IGI Global, 2017, pp. 541-561. https://doi.org/10.4018/978-1-5225-2229-4.ch023

APA

Gharbia, R. & Hassanien, A. E. (2017). Swarm Intelligence Based on Remote Sensing Image Fusion: Comparison between the Particle Swarm Optimization and the Flower Pollination Algorithm. In A. Hassanien & T. Gaber (Eds.), Handbook of Research on Machine Learning Innovations and Trends (pp. 541-561). IGI Global. https://doi.org/10.4018/978-1-5225-2229-4.ch023

Chicago

Gharbia, Reham, and Aboul Ella Hassanien. "Swarm Intelligence Based on Remote Sensing Image Fusion: Comparison between the Particle Swarm Optimization and the Flower Pollination Algorithm." In Handbook of Research on Machine Learning Innovations and Trends, edited by Aboul Ella Hassanien and Tarek Gaber, 541-561. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2229-4.ch023

Export Reference

Mendeley
Favorite

Abstract

This chapter presents a remote sensing image fusion based on swarm intelligence. Image fusion is combining multi-sensor images in a single image that has most informative. Remote sensing image fusion is an effective way to extract a large volume of data from multisource images. However, traditional image fusion approaches cannot meet the requirements of applications because they can lose spatial information or distort spectral characteristics. The core of the image fusion is image fusion rules. The main challenge is getting suitable weight of fusion rule. This chapter proposes swarm intelligence to optimize the image fusion rule. Swarm intelligence algorithms are a family of global optimizers inspired by swarm phenomena in nature and have shown better performance. In this chapter, two remote sensing image fusion based on swarm intelligence algorithms, Particle Swarm Optimization (PSO) and flower pollination algorithm are presented to get an adaptive image fusion rule and comparative between them.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.