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Analysis of objective video quality metric using wavelet transform

In this paper, we investigate the performance of an objective video quality assessment method using the wavelet transform for a large data set. The objective video quality assessment utilizes the wavelet transform, which is applied to each frame of source and processed videos in order to compute spatial frequency components. Then, the difference (squared error) of the wavelet coefficients in each subband is computed and summed. By repeating this procedure to the entire frames of a video, a sequence of difference vectors and the average vector are obtained. Each component of the average vector represents a difference in a certain spatial frequency. In order to take into account the temporal frequencies, a modified 3-D wavelet transform can be applied. Although this evaluation method provides a good performance for training data, its performance for new test videos remains to be seen due to a large number of parameters. In this paper, we apply the method to a large video data set and analyze the performance.