In inhomogeneous objects, a highlight is a linear combination of specular and diffuse reflection components. A number of methods have been proposed to separate these two 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 information. One of the basic ideas is to iteratively compare the intensity logarithmic differentiation of an input image and its specular-free image. Specular-free image is an image that has exactly the same geometrical profile as  the diffuse component of the input image, and that can be generated by shifting each pixel's intensity and maximum chromaticity non-linearly. Unlike existing methods using a single image, all processes in the proposed method are done locally, involving a maximum of only two neighboring pixels. This local operation is useful for  handle textured objects with complex multicolored scenes. Our evaluations by comparison with the results of polarizing filters show the effectiveness of the proposed method.