Automatic image quality improvement for videoconferencing

In videoconferencing, the image quality is significantly affected by the illumination condition. Unsatisfactory illumination conditions may lead to underexposure or overexposure of the area of interest, in particular a human face. To resolve this issue, we propose a solution to improve image quality automatically by correcting exposure and enhancing contrast. Our work is characterized by a method for automatically building a skin-color model and a novel contrast enhancement approach. Some techniques that can reduce the computational cost are also introduced. Experimental results show that obvious improvement in image quality is achieved while the computation overhead is very small. The proposed solution can be integrated into videoconferencing systems and is especially suitable for scenarios where low-complexity computing is required.