THE PERFORMANCE OF DEVELOPED INTENSITY HUE SATURATION FUSION OF MULTISPECTRAL AND PANCHROMATIC IMAGES USING PELICAN OPTIMIZATION ALGORITHM

Abstract

Background:In medical applications, image fusion has become a popular approach for improving image interpretation quality.It comprises combining data from two or more object pictures to create a single, more informative image that is suitable for computer analysis or visual perception. Material and methods:The datasets of two thousand eight hundred, which consist of images and postures of randomly selected students of Department of Computer Science, Ladoke Akintola University of Technology, were acquired using a SAMSUNG 315 digital camera and normalized to a uniform size of 300 x 300 pixels.Sixty percent of the images were used for the training while the remaining forty percent were used for testing purposes. Results:The results showed that at optimum threshold value of 0.85, the Enhanced Intensity Saturation (EIHS) gave 98.44%, 98.22%, 97.78%, 96.90, 107.75s and 14.81% for recognition accuracy, Sensitivity, Specificity, Precision, Computational Speed and False Positive Rate respectively.The standard Intensity Hue Saturation (IHS) produced 96.44%, 96.00%, 95.78%, 95.56%, 120.0s and 8.89% for recognition accuracy, Sensitivity, Specificity, Precision, computational speed and False Positive Rate respectively Conclusion: It was concluded that the performance of the developed model of Enhanced Intensity Hue Saturation (EIHS) based model could be very useful and reduce crime and fraudulent cases.