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Very high resolution (VHR) images are appreciated for their high-level details, which significantly increase their application potential. However, typically, VHR images are affected by the presence of shadows. An attempt solution to the problem of shadows is to restore shadow-contaminated regions by compensating the value of shaded pixels. Unfortunately, it may happen that not all shadow areas are possible to restore. In this paper, we propose different criteria useful to help in understanding a priori if it is possible or not to reconstruct a specific shadow area. An ideal reconstructability criterion should not tolerate that an unreconstructable shadow area is assigned as reconstructable and, at the same time, should maximize the probability of detection of reconstructable areas. Several evaluation criteria working at the pixel and textural levels are presented. Furthermore, in order to select the best criteria, a fuzzy logic combination of the criteria is explored. A thorough experimental analysis is reported and discussed. It leads to the definition of a final global index based on the fusion of two single criteria, which are the Kullback–Leibler divergence and the angular second-moment difference.