The use of ROC and AUC in the validation of objective image fusion evaluation metrics

Objective image fusion evaluation metrics play a vital role in choosing proper fusion algorithms and optimizing parameters in the field of image fusion. However, little effort has been made on their validation. In this paper, we proposed a novel validation method using ROC (Receiver Operating Characteristic) curve and AUC (the Area Under the ROC Curve). The proposed method takes the predicted quality scores into account rather than just counting how many fused images are correctly evaluated, which makes it more discriminating than other existing methods. Experimental results show that it is a reliable and precise validation method of objective fusion evaluation metrics. This paper is of particular interest to researchers focusing on objective fusion metric designing and those constructing image sets for testing objective fusion evaluation metrics.