No-Reference Image and Video Quality Assessment

Image and video quality assessment has become an increasingly important subject in digital video coding and transmission scenarios, such as digital television. In this context, a special interest has been put on no-reference objective quality assessment metrics, since they are suitable for real-time quality monitoring once the video delivery system is settled. This Thesis proposes new no-reference quality assessment metrics for images and video. The main goal of the proposed techniques is to estimate the quality of lossy DCT-based encoded video. The proposed metrics share the same key idea: based on elements extracted from the bitstream of the encoded images or video arriving at the point where quality assessment has to be performed, an estimate of the quantization error associated to each DCT coefficient is obtained. Those estimates are perceptually weighted and combined in order to obtain a quality score for the image or video under analysis. The Thesis starts by proposing a technique based on watermarking, that evolves to a technique based on natural image statistics only. The results produced by the metrics are close to and well correlated with subjective quality assessment data.