Contrast Enhanced Low-light Visible and Infrared Image Fusion

Multi-modal image fusion objective is to combine complementary information obtained from multiple modalities into a single representation with increased reliability and interpretation. The images obtained from low-light visible cameras containing fine details of the scene and infrared cameras with high contrast details are the two modalities considered for fusion. In this paper, the low-light images with low target contrast are enhanced by using the phenomenon of stochastic resonance prior to fusion. Entropy is used as a measure to tune iteratively the coefficients using bistable system parameters. The combined advantage of multi scale decomposition approach and principal component analysis is utilized for the fusion of enhanced low-light visible and infrared images. Experimental results were carried out on different image datasets and analysis of the proposed methods were discussed.