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 (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. [ABSTRACT FROM AUTHOR]