A human perception inspired quality metric for image fusion based on regional information

Comparative evaluation of fused images is a critical step to evaluate the relative performance of different image fusion algorithms. Human visual inspection is often used to assess the quality of fused images. In this paper, we propose some variants of a new image quality metric based on the human vision system (HVS). The proposed measures evaluate the quality of a fused image by comparing its visual differences with the source images and require no knowledge of the ground truth. First, the images are divided into different local regions. These regional images are then transformed to the frequency domain. Second, the difference between the local regional images in frequency domain is weighted with a human contrast sensitivity function (CSF). The quality of a local regional image is obtained by computing the MSE of the weighted difference images obtained from the fused regional image and source regional images. Finally, the quality of a fused image is the weighted summation of the local regional images quality measures. Our experimental results show that these metrics are consistent with perceptually obtained results.