Image segmentation with simultaneous illumination and reflectance estimation: An energy minimization approach

Spatial intensity variations caused by illumination changes have been a challenge for image segmentation and many other computer vision tasks. This paper presents a novel method for image segmentation with simultaneous estimation of illumination and reflectance images. The proposed method is based on the composition of an observed scene image with an illumination component and a reflectance component, known as intrinsic images. We define an energy functional in terms of an illumination image, the membership functions of the regions, and the corresponding reflectance constants of the regions in the scene. This energy is convex in each of its variables. By minimizing the energy, image segmentation result is obtained in the form of the membership functions of the regions. The illumination and reflectance components of the observed image are estimated simultaneously as the result of energy minimization. With illumination taken into account, the proposed method is able to segment images with non-uniform intensities caused by spatial variations in illumination. Comparisons with the state-of-the-art piecewise smooth model demonstrate the superior performance of our method.