Development of pyramidal transform based image fusion technique with improved SSIM with underwater images in comparison with wavelet transform based image fusion technique.

To produce more accurate photographs than any single image could offer, image fusion uses information from many photos of the same topic taken at the same time or at different times. The purpose of this research is to create a novel transform-domain-based method of picture fusion. In this study, we suggest and investigate a method for fusing several images using a pyramidal transform. Using SSIM and UIQI values, 30 samples are compared to a wavelet transform-based image fusion approach. With a significance level of 0.05 and a 95% confidence interval, the enrollment ratio is fixed at 1. Two metrics—SSIM and the Universal Image Quality Index Measure—are used to evaluate image fusion performance (UIQI). When it comes to evaluating the efficacy of image fusion algorithms, higher SSIM and UIQI values are preferable. Mean SSIM values obtained through the pyramidal transform are 2.3283 (p=0.098) and mean UIQI values obtained via the wavelet transform are 30.0767 (p=0.098). (percent). The trials conducted in MATLAB and the statistical analysis performed in IBM-SPSS have led to the conclusion that the pyramidal transform based image fusion approach is superior than the wavelet transform based technique. [ABSTRACT FROM AUTHOR]