Image Fusion Based on Improved Region Growing and Guided Filtering

Aiming at the problems of insufficient target extraction and loss of details in infrared and visible image fusion algorithm, an infrared and visible image fusion method based on improved region growing method (IRG) and guided filtering is proposed. First, use IRG to extract targets from infrared images, then use NSST for infrared and visible images, and conduct guided filtering for the obtained low-frequency and high- frequency components. The filtered infrared and visible low-frequency components get low-frequency fusion coefficients through IRG based fusion rules, and the enhanced high-frequency components get high-frequency fusion coefficients through dual- channel spiking cortical model (DCSCM). Finally, the fused image is obtained by NSST inverse transform. The fused image is evaluated with subjective evaluation and 6 common objective evaluation indexes. The experimental results show that the proposed algorithm has obvious advantages in subjective and objective evaluation, such as prominent target, clear background information, strong detail retention ability.