Towards a visual quality metric for digital video

The advent of widespread distribution of digital video creates a need for automated methods for evaluating the visual quality of digital video. In previous work, we have developed visual quality metrics for evaluating, controlling, and optimizing the quality of compressed still images
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. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic signals. Here I describe a new video quality metric that is an extension of these still image metrics into the time domain. Like the still image metrics, it is based on the Discrete Cosine Transform. An effort has been made to minimize the amount of memory and computation required by the metric, in order that might be applied in the widest range of applications. To calibrate the basic sensitivity of this metric to spatial and temporal signals we have made measurements of visual thresholds for temporally varying samples of DCT quantization noise.