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Video transmitted over an error-prone network may be received at the decoder with degradations due to packet losses. No-reference quality monitoring algorithms are the most practical way to measure the quality of the received video, since they do not impose any change with respect to the network architecture. Conventionally, these methods assume the availability of the corrupted bitstream. In some situations this is not possible, e.g., because the bitstream is encrypted or processed by third-party decoders, and only the decoded pixel values can be used. The major issue in this scenario is the lack of knowledge about which regions of the video have been actually lost, which is a fundamental ingredient for estimating channel-induced distortion. In this paper, we propose a maximum a posteriori estimation of the pattern of lost macroblocks, which assumes the knowledge of the decoded pixels only. This information can be used as input to a no-reference quality monitoring system, which produces an accurate estimate of the mean-square-error (MSE) distortion introduced by channel errors. The results of the proposed method are well correlated with the MSE distortion computed in full-reference mode, with a linear correlation coefficient equal to 0.9 at frame level and 0.98 at sequence level. [ABSTRACT FROM PUBLISHER]

Wyner–Ziv video coding (WZVC) is a newly emerged video coding scheme which compresses the input video frames with the side information (SI) frames only available at the decoder. WZVC exploits the statistics between the source frame and the SI frame at the decoder by utilizing their correlation information. This correlation information is important but also difficult to estimate due to the absence of the SI frame at the encoder, and the lack of the source frame at the decoder. In this paper, we focus on this problem and propose a novel transform-domain adaptive correlation estimation method called TRACE for WZVC. In TRACE, the correlation information is progressively learned during the decoding process of each frame. Within TRACE, we also propose a convex optimization based band-level correlation estimation method which is optimal in the sense of minimizing the theoretical bit rate. Experiments suggest that, when applied in motion compensated interpolation-based low complexity WZVC, TRACE yields competitive results against the state-of-the-art correlation estimation algorithms. More importantly, different from the existing coefficient-level correlation estimation algorithms, the proposed TRACE can be applied in many other WZVC schemes and can provide considerable gain over the popular band-level correlation estimation methods. [ABSTRACT FROM PUBLISHER]