Abstract

In videoconferencing, the image quality is significantly affected by the illumination condition.Unsatisfactory illumination conditions may lead to underexposure or overexposure of the area ofinterest, in particular a human face. To resolve this issue, we propose a solution to automaticallyimprove image quality by correcting exposure and enhancing contrast. Our work is characterized by amethod for automatically building a skin-color model and a novel contrast enhancement approach.Some techniqu an reduce the computational cost are also introduced. Experimental results show thatobvious improvement in image quality is achieved while the computation overhead is very small. Theproposed solution can be integrated into videoconferencing systems and is especially suitable forscenarios where low-complexity computing is required. From our experiments, it is found that there isan optimal resolution to balance between speed and accuracy, while we show in our experiments thatthe resolution has apparent influence on both the accuracy and the computing time.

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