Separating reflection components of textured surfaces using a single image

The presence of highlights, which in dielectric inhomogeneous objects are linear combination of specular and diffuse reflection components, is inevitable. A number of methods have been developed to separate these reflection components. To our knowledge, all methods that use a single input image require explicit color segmentation to deal with multicolored surfaces. Unfortunately, for complex textured images, current color segmentation algorithms are still problematic to segment correctly. Consequently, a method without explicit color segmentation becomes indispensable, and this paper presents such a method. The method is based solely on colors, particularly chromaticity, without requiring any geometrical parameter information. One of the basic ideas is to compare the intensity logarithmic differentiation of specular-free images and input images iteratively. The specular-free image is a pseudo-code of diffuse components that can be generated by shifting a pixel´s intensity and chromaticity nonlinearly while retaining its hue. All processes in the method are done locally, involving a maximum of only two pixels. The experimental results on natural images show that the proposed method is accurate and robust under known scene illumination chromaticity. Unlike the existing methods that use a single image, our method is effective for textured objects with complex multicolored scenes.