A multidirectional-difference-hash-based image clutter metric for targeting performance

Quantification of image clutter plays an important role in predicting target acquisition performances of a photoelectric imaging system due to the strong effect of optoelectronic image clutter. Accuracy in predicting the targeting performance of previous reported clutter metrics was relatively low because of disadvantages, such as lack of ability to accurately quantify the image with complex clutters and threshold selection problem. To address this problem, a novel multidirectional-difference-Hash-based (MDHash-based) image clutter metric is proposed in this paper. Initially, an image similarity measure method based on multidirectional difference hash is established. Then, this method is applied to the quantification of image clutter, and an MDHash-based image clutter metric is obtained. A comparative experiment is conducted using Search-2 dataset. Results show that the proposed clutter metric correlates effectively with probability of detection, false alarm rate, and search time of observers.