The FVR(frequency domain volume rendering) approach explores a 3D data set faster than traditional spatial domain methods because of its innate lower computation al complexity. Unfortunately, images produced by the FVR methods always lack occlusion or depth cue since it is hard to represent and utilize the depth information within frequency domain efficiently. Some researchers have sought to make a remedy of this by means such as of linear depth cuing. This approach, however, is still far different from the conventional spatial domain methods which, using the color composition technique, generate images with realistic depth effect. In this paper, the discrete color composition of spatial domain algorithms is reviewed, before an analytical result of the continuous color composition is deducted. These equations become feasible for calculating in frequency domain on certain assumptions such as the transparency inside the data set is distributed homogeneously. The authors continue to discuss the detail implementation of this new algorithm based on their previous work, the substance classification FVR approach. The experimental result shows that both the computational complexity and the run-time cost are kept at the same level of former FVR algorithms.