A New Spatial Activity Metric for Film Contents

The masking property of human vision systems has been successfully applied in various image/video applications. To invoke the spatial masking effect, it is important to design a metric that effectively identifies the spatial activity of a region. This metric indicates which areas are more textured and more artifacts can be masked. We review three widely used metrics and evaluate their performance in context of film content. We observe that these metrics have strong dependencies on the brightness. More specifically, for smooth areas with film grain, these metrics usually assign greater degrees of texture to the bright regions and lower degrees to dark ones. This causes problems in the bright areas that are mistakenly identified as more textured than the dark areas. Utilizing the property of film grain, we explain the origin of this dependency and propose a new spatial activity metric that removes the dependency on the brightness. In our simulation, we use this new metric in the rate control algorithm of a MPEG-2 video encoder. The result shows more homogeneous film grain in the reconstructed pictures and improved visual quality.