In order to improve the visualization effect of the void evolution of materials, an adaptive color mapping method based on data characteristics was proposed. Firstly, a number of control points were selected in the CIELAB color space to form an initial color path. Then, based on the proportion of the data characteristic values, the positions of control points were optimized and the color path was adjusted according to the constraints such as uniformity of color difference and consistency of brightness, so as to meet the requirement of control points following the data adaptively. Finally, the distribution of the perceptual difference sum was remapped by the equalization algorithm, and the perceptual uniformity of the color mapping was optimized to form the final color map. The experimental results show that, compared with traditional color mapping methods which only consider the color space and ignore the diversity of data, the proposed adaptive color mapping method has better identifiability of the characteristics of visualization results by fully considering the color proportion, the number of control points and self-adaptation, and guarantees the perceptual uniformity of the visualization results of the void evolution, improving the accuracy of visualization results and reduces the time required to observe effective information.