Accuracy of the spider model in decomposing layered surfaces

The surface of most natural objects is composed of two or more layers whose optical properties jointly determine the surface's overall reflectance. Light transmission through these layers can be approximated by using the Lambert-Beer (LB) model, which provides a good trade-off between the accuracy and simplicity to handle layer decomposition. Recently, a layer decomposition based on the LB-based model is proposed. Assuming surfaces with two layers, it estimates the reflectance of top and bottom layers, as well as the opacity of the top layer. The method introduces the “spider model”, which is named after the color distribution in the RGB space that resembles the shape of spiders. In this paper, we intend to verify the accuracy of the spider model and the optical model where it is based on (i.e., the LB-based model). We verify the LB-based model by comparing to the Kubelka-Munk (KM) model, which has previously been shown to be reliably accurate. The benefits of layer decomposition are easy to notice. First, many computer vision algorithms assume a single layer, and tend to fail when encountering multi-layered surfaces. Second, knowing the optical properties of each layer can provide further knowledge of the target objects.