Morphological center operator based infrared and visible image fusion through correlation coefficient

It is important to well maintain the information of infrared (IR) and visible images, including image regions and details, in a fusion image. To be effective for fusion, an algorithm for fusion IR and visible images based on the morphological center operator through feature extraction and correlation coefficient is given. This paper utilizes the contrast enlargement strategy for fusion. Firstly, the morphological center or anti-center operator identifies the bright and dim features of the IR and visible images, and these identified features are used for fusion based on the correlation coefficient. Secondly, the multi-scale morphological theory is employed to extract the multi-scale features through the correlation coefficient based strategy to form the final fusion features. Finally, the extracted final fusion features are combined to form the final fusion image by utilizing the contrast enlargement strategy. Because of the effectively feature identifying by the morphological center and anti-center operators, the proposed algorithm has good performance for IR and visible image fusion. Experiments on different IR and visible images verified that the proposed algorithm performed effectively.