Pixel Level Image Fusion: A Neuro-Fuzzy Approach

Abstract

Image fusion is done for integrating images obtained from different sensors, which outputs a single image containing all relevant data from the source images. Five different image fusion algorithms, SWT, fuzzy, Neuro-Fuzzy, Fuzzylet and Neuro-Fuzzylet algorithms has been discussed and tested with two datasets (mono-spectral and multi-spectral). The results are compared using fusion quality performance evaluation metrics. It was observed that Neuro-Fuzzy gives better results than Fuzzy and SWT. Fuzzylet and Neuro-Fuzzylet were obtained by combining Fuzzy and Neuro-Fuzzy respectively with SWT. It was observed that Fuzzylet gives better results for mono-spectral images and on the other hand, Neuro-Fuzzylet had given better results for multi-spectral images at the cost of execution time.