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Reducing dynamic false contour (DFC) is quite needed for image quality enhancement under the address display separate (ADS) driving scheme, while keeping a good gray scale rendition (GSR). The conventional method of reducing DFC effectively by using a limited number of graylevel deteriorates GSR quality in a still or slowly moving images in which DFC seldom occurs. To optimize DFC reduction and GSR improvement simultaneously, this paper proposes an adaptive gray-level method, in which input images are first classified by the motion information and one of five different gray-level systems is adaptively chosen depending on the classification result. The skin color area, which is sensitive to DFC artifacts, are detected and specially treated for further enhancement of picture quality.