| Summary: | 碩士 === 國立中正大學 === 資訊工程研究所 === 106 === Nowadays, Internet is booming and the perception of video quality by video providers and users is becoming more important, but limit by the bandwidth of network transmission. No reference video quality computation is the best and well-known in three types of video quality assessment metrics. In this study, the proposed video quality computation metric is based on no reference and extracted spatial, temporal, transform, and spatiotemporal features as the basis for predicting quality scores. First, edge detection and blockiness are extracted as the spatial features and difference of luminance and motion are extracted as temporal features. The pairwise products of discrete cosine transform and wavelet transform are extracted to enhance the center point pixel and surrounding neighbor pixels, and are regarded as transform features. Considering that spatial and temporal information can extracted simultaneously, the statistical properties of trajectory and three-dimensional discrete cosine transform are taken as spatiotemporal features. Finally, support vector regression is utilized to predict the final quality score. This experiment using LIVE video quality assessment database and experimental results show that the results have better results than other existing metrics.
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