Infrared and visual image fusion via multi-modal decomposition and PCNN in gradient domain fusion measure

Abstract

Infrared and visual image fusion aims to obtain a complex image which contains more recognizable information. To obtain the complex image, a fusion algorithm via multi-modal decomposition and pulse-coupled neural network (PCNN) in gradient domain fusion measure is proposed. Firstly, the source images are decomposed into three layers through the decomposition model. Then, a gradient domain PCNN fusion measure is employed in the three layers. Finally, the fused image is reconstructed through the three fused layers. Experimental results demonstrate that the proposed algorithm performs effectively in both qualitative and quantitative measures.