Varying illumination condition is a challenging problem for face recognition and synthesis. The illumination re-rendering technique allows aligning the illumination effects of facial images or relighting them as expected. In this paper, we propose an improved illumination re-rendering method based on more accurate mapping of facial images in the parametric illumination space. This will make the parameter-based illumination alignment more reliable. A clustering-based criterion is designed to evaluate its parameter estimation precision. To guide the image re-rendering between any a parameter pair, an intermediate image called the illumination transition image (ITI) is defined to represent both the illumination variation information and the personspecific facial shape features. The extensive experimental results verify the proposed method outperforms the quotient image approach on both parameter precision and rendering quality.