Investigation of image fusion methods for helicopter day, night and all weather operation

The combination of passive millimeter wave (PMMW) and infrared (IR) sensor images could help to improve pilot vision especially in poor weather condition. The performance of common image fusion methods and their fusion rules are evaluated with a view to determine their suitability for helicopter day, night and all weather operation. The major criterion for quantifying a fusion method is its ability to utilize complementary and reverse contrast information as well as reduce noise without introducing artifacts. Both visual inspection and the objective evaluation methods of entropy, mutual information, standard deviation, peak signal to noise ratio, root mean square error and computation time were used. Experimental results show that Laplacian pyramid based on maximum coefficient selection with consistency verification rule gives better performance. This method is applied to simulated PMMW and IR images in both heavy fog and heavy rain condition and is found to provide images that could assist a pilot operating in poor weather conditions.