In order to characterize the performance of visible digital imaging systems in the laboratory, in the field and in simulation, the use of fractal test-targets has been optimized. This work is based on the previous achievements in the use of binary fractal targets (2014) and the Corner-Point (CP) resolution criterion (2017), for DRI range modeling of optronic cameras. The principle is to resume from the process of multi-scale fractal calculation of the binary target, to extend it in the case of a multi-level of gray. The distribution of CP contrasts by scale is then adapted to two constraints, on the one hand the measurement accuracy and on the other hand the criterion definition of the operational task evaluated for the camera. A target will be specifically designed to accommodate an operational need, such as the identification of vehicles or handheld weapon. The exploitation of the fractal target degraded by the imager is carried out by the comparison of CP by scales with the original target, after an image registration phase, facilitated by an original Yin-Yang design of the target at its lowest CP scale. The main metric for assessing DRI range is the Resolved Contrast Function (RCF), obtained from the multi-scale CP Probability of Correct Resolution. In the first part of the paper, the principles of design and exploitation of the target are presented, applied to an example of a DRI range assessment of a camera coupled to image restoration processing. In a second part, the use of this evaluation technique is developed in the example of digital image fusion systems, from two bands with its own optronic characteristics and some non-linear digital processing. This work, carried out in simulation using the FUSIM software, allows to establish a selection of the optimal combinations (pre-processing, fusion processing) offering the best RCF.