Satellite image fusion based on modified central force optimization

Nowadays, optimization has become a brand methodology for different applications. One of the most promising fields for application of optimization is the image processing field, especially image fusion. A new effective deterministic optimization technique is the modified central force optimization (...

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Bibliographic Details
Published in:Multimedia tools and applications 2020-08, Vol.79 (29-30), p.21129-21154
Main Authors: Talal, Tamer M., Attiya, Gamal, Metwalli, Mohamed R., Abd El-Samie, Fathi E., Dessouky, Moawad I.
Format: Article
Language:English
Subjects:
Computer Communication Networks
Computer Science
Computer vision
Data Structures and Information Theory
Discrete Wavelet Transform
Image processing
Multimedia Information Systems
Night vision
Optimization
Optimization techniques
Satellite imagery
Saturation (color)
Special Purpose and Application-Based Systems
Target recognition
Wavelet transforms
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Summary:Nowadays, optimization has become a brand methodology for different applications. One of the most promising fields for application of optimization is the image processing field, especially image fusion. A new effective deterministic optimization technique is the modified central force optimization (MCFO) that overcomes the low convergence rate drawback of the central force optimization (CFO). In this paper, the MCFO is applied with standard image fusion methods as a novel brand to improve the fusion efficiency either qualitatively or quantitatively. Intensity-hue-saturation (IHS), high-pass filtering (HPF), and discrete wavelet transform (DWT) are powerful standard techniques for satellite image fusion that are implemented with MCFO optimization in this paper. They are performed on satellite panchromatic (PAN) and multispectral (MS) images. The target of using the MCFO is to reduce some spectral and spatial distortions that may occur without optimization. Different qualitative indices have been used to validate the proposed approach comprising optimization for satellite image fusion.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-019-08471-7