In this paper, we describe the problem of retrospective shading correction, which is a necessary pre-processing step in many tasks of image analysis. Eight algorithms are implemented and compared. The performance of the algorithms was analyzed on three sets of differently structured synthetic shaded and shading-free images. The results show that the entropy minimization (EMI) method outperforms the other methods in terms of the reduction of true intensity variations and preservation of intensity characteristics of the shading-free images. The strength of EMI is especially apparent when applied to images containing large-scale objects.