A structural difference based image clutter metric with brain cognitive model constraints

Previous clutter metrics have less than the desired accuracy in predicting targeting performance, in this paper, a structural difference based image clutter metric is proposed based on the given definition of image clutter metric. According to the sensitivity of human visual perception to image structural information, a structural similarity measure between the target and clutter images is firstly established. Previous clutter metrics not considering brain cognitive characteristics, we define an information content weight measure by introducing the widely accepted brain cognitive information extracting model in the field of image quality assessment (IQA), and then, pool the structural similarity measure to be a clutter metric, which can be entitled BSD metric. Comparative field tests show that BSD metric makes a more significant improvement than previously proposed metrics in predicting target acquisition performance including detection probability and search time.

► We give a new definition of image clutter metric. ► Propose a structural difference based image clutter metric. ► The metric improves the precision of targeting performance prediction models. ► Including: detection probability, false alarm probability and search time. ► Pearson linear correlation coefficients are up to 0.879, 0.847 and 0.881.