Predator prey optimizer and DTCWT for multimodal medical image fusion

In this paper, we propose a hybrid algorithm of Predator Prey Optimizer (PPO) with a multi-resolution transform, Dual Tree Complex Wavelet Transform (DTCWT). This hybridizing approach, which combine positive features of the two algorithms, aims to solve the problem of multimodal medical image fusion. The source images to be fused are decomposed by this new algorithm into high-frequency and low-frequency coefficients. Then we proceed by fusing these two types of coefficients in different manners: high-frequency coefficients are fused by the absolute maximum method and the low-frequency coefficients are fused by weighted average method in which the weights are estimated and optimized by the predator prey optimizer to gain optimal result. We demonstrate by the experiments that this algorithm provides a robust and efficient way to fuse multimodal medical images compared to existing Wavelet Transform algorithms because it gives promising results and it is better to obtain more information in fused image.