Towards an automatic correction of over-exposure in photographs: Application to tone-mapping

A common artifact in photographs is over-exposure due to bright scene features exceeding the abilities of the camera, and causing image areas to appear flat and lacking in detail. Although a wider luminance range could be captured with HDR techniques, this is often not possible, especially in moving scenes. To address this issue, we propose a novel solution for recovering lost details in clipped and over-exposed areas by taking advantage of channel cross-correlation in RGB images. To automate our approach we propose two improvements: (1) using the image white point, we adaptively estimate a clipping threshold value per image, and (2) to better understand the forms of over-exposure, for an optimal selection of parameters, we construct an image database focusing on over-exposed areas and automatically classify over-exposure as light sources, specular highlights or diffuse surfaces. We evaluate our solution using objective metrics and a subjective study based on an ITU standard protocol, showing that our correction leads to improved results compared to previous related techniques. We explore several potential applications of our method, including extending to video as well as using it as a preprocessing step prior to reverse tone mapping.