Usually, when contour enhancement is performed on an image, it is necessary to emphasize the image contour by widening the gray level gap or highlighting sensitive gray levels. The common method is to use the histogram regularization method, but this method will face the problem that the transformed histogram cannot obtain a high overlap with the target histogram, which leads to the insufficient effect of contour enhancement. In this paper, we propose a forced probabilistic histogram transformation method, which uses probabilistic transformation to achieve a forced mapping of the same gray level to different gray levels of the target histogram, effectively mapping the gray levels into the restricted interval while obtaining a higher degree of overlap. The effectiveness of the forced probability histogram regularization algorithm be derived from the experiments of actual contour enhancement and the comparison of SML (Single Mapping Law) histogram regularization method in terms of overlap and time complication .