Single Image Specular Highlight Removal on Natural Scenes

Abstract

Previous methods of highlight removal in image processing have exclusively addressed images taken in specific illumination environments. However, most of these methods have limitations in natural scenes and thus, introduce artifacts to nature images. In this work, we propose a specular highlight removal method that is applicable to natural scene image. Firstly, we decompose the input image into a reflectance image and an illumination image based on Retinex theory, and show that the illumination image of natural scene is obviously different from that of commonly used experimental scene. Then, the smooth features of the input image are extracted to help estimate the specular reflection coefficient in chromaticity space. Finally, the space transformation is used to calculate the specular components and the highlight removal is achieved by subtracting the specular reflection component from the original image. The experimental results show that our method outperforms most of existing methods on natural scene images, especially in some challenging scenarios with saturated pixels and complex textures.