Scope of validity of PSNR in image/video quality assessment

Experimental data are presented that clearly demonstrate the scope of application of peak signal-to-noise ratio (PSNR) as a video quality metric. It is shown that as long as the video content and the codec type are not changed, PSNR is a valid quality measure. However, when the content is changed, correlation between subjective quality and PSNR is highly reduced. Hence PSNR cannot be a reliable method for assessing the video quality across different video contents.     

MDVQM: A novel multidimensional no-reference video quality metric for video transcoding

In this paper, we study the impact of quantization, frame dropping and spatial down-sampling on the perceived quality of compressed video streams. Based on the analysis of quality ratings obtained from extensive subjective tests, we propose a no-reference metric (named MDVQM) for video quality estimation in the presence of both spatial and temporal quality impairments. The proposed metric is based on the per-pixel bitrate of the encoded stream and selected spatial and temporal activity measures extracted from the video content. All the values required to compute the proposed video quality metric can be obtained without using the original reference video which makes the metric for instance useful for making transcoding decisions in a wireless video transmission scenario. Different from comparable metrics in the literature, we have also considered the case when both frame rate and frame size are changed simultaneously. The validation results show that the proposed metric provides more accurate estimation of the video quality than the state of the art metrics.     

Robust spatio-temporal error concealment for packet- lossy H.264 video transmission

1 Introduction With the ubiquitous use of Internet and the deployment of next generation of networks, video communications are increa- singly becoming the major services in demand. Unlike data transmission, video communication is essentially time-sensitiv…     

Vision-model-based impairment metric to evaluate blocking artifactsin digital video

In this paper investigations are conducted to simplify and refine a vision-model-based video quality metric without compromising its prediction accuracy. Unlike other vision-model-based quality metrics, the proposed metric is parameterized using subjective quality assessment data recently provided by the Video Quality Experts Group. The quality metric is able to generate a perceptual distortion map for each and every video frame. A perceptual blocking distortion metric (PBDM) is introduced which utilizes this simplified quality metric. The PBDM is formulated based on the observation that blocking artifacts are noticeable only in certain regions of a picture. A method to segment blocking dominant regions is devised, and perceptual distortions in these regions are summed up to form an objective measure of blocking artifacts. Subjective and objective tests are conducted and the performance of the PBDM is assessed by a number of measures such as the Spearman rank-order correlation, the Pearson correlation, and the average absolute error The results show a strong correlation between the objective blocking ratings and the mean opinion scores on blocking artifacts     

A new perceptual quality metric for compressed video based on mean squared error

A full reference objective quality metric that predicts perceived quality of compressed video is proposed. The metric estimates the mean opinion score (MOS) based on spatio-temporal activity and the mean squared error (MSE) between original and compressed video sequences. The proposed metric has been tested on multimedia sequences of common intermediate format (CIF) resolution compressed at a wide range of bit rates using the H264/AVC coding standard. This metric shows a higher correlation with subjective quality ratings (MOS) than popular metrics such as peak signal to noise ratio (PSNR), video structural similarity metric (VSSIM), national telecommunication and information administration’s video quality metric (NTIA/ITS VQM) and PSNRplus. This algorithm is particularly useful for real-time quality estimation of multimedia sequences compressed using block-based video coding schemes and all the parameters of the metric can be calculated automatically with a modest amount of processing overhead.     

Evolution strategy based rate controlling for off-line video coding

An intelligent rate control technique for H.264/AVC using the subjective quality of video is proposed. A subjective video quality metric is used with an evolution strategy algorithm, which is capable of identifying the best possible quantisation parameters for each frame/macroblock to encode the video sequence such that it would maximise the subjective quality of the entire video sequence subjected to the target bit rate. Simulation results show that up to 40% bit rate saving can be achieved with the proposed technique at the same video quality.     

Joint reference frame inter-mode selection for fast H.264 video coding

The H.264/AVC video coding standard uses multiple reference frames and variable-size macroblock partitions in inter-prediction. This flexibility allows the standard to achieve excellent rate-distortion performance at the cost of high encoding complexity. We present an algorithm for fast joint selection of the reference frames and macroblock partitions in rate-distortion-based coding. Experimental results for eight standard test video sequences show that, compared with exhaustive search, our algorithm can save up to 74.9 % of the encoding time with negligible loss in rate-distortion performance. The presented algorithm is also evaluated using a subjective assessment metric; quality evaluation measures based on user satisfaction. Diverse types of video sequences were used with different frame rates, quantization parameters, and resolutions. The effects of changing bit rate and resolution on compression efficiency and viewers’ satisfaction are also presented. Results show that our algorithm provides high scores of perceptual satisfaction that are significantly affected by the compression technique. As a result, we claim that our algorithm presents original and significant enhancement compared with exhaustive search. In addition, overall test results showed that our technique outperformed three of the best previously proposed methods and gave higher viewer satisfaction.     

Applications and improvement of H.264 in medical video compression

This paper aims at applying H.264 in medical video compression applications and improving the H.264 rate control algorithm with better perceptual quality. First, H.264 is briefly reviewed and introduced to the area of medical video compression. Second, a new motion complexity (MC) measure is defined to express the complexity of motion contents in a video frame, and a new H.264 rate control scheme with the MC measure and perceptual bit allocation is proposed for medical video compression. Third, two sets of experiments are conducted: the comparison between MPEG-4 and H.264, and the comparison between JVT-H014 , which is the H.264 adopted rate control algorithm, and our proposed rate control scheme. The first set of experiments shows that compared with MPEG-4, H.264 can achieve a significant average peak signal-to-noise ratio (PSNR) gain of up to 4.35 dB for the test medical video sequences, and thus is much more effective when applied in medical video compression. The second set of experiments shows that compared with H014, the proposed rate control scheme can achieve better perceptual video quality, with an average PSNR gain of up to 0.19 dB for the test medical video sequences.     

A parametric model for perceptual video quality estimation

In this paper, a parametric model is proposed which provides estimation for the perceived quality of video, coded with different codecs, at any bit rate and display format. The video quality metric used is one of the standardized Full Reference models in Recommendations ITU-T J.144 and ITU-R BT.1683. The proposed model is based on the video quality estimation described in Recommendation ITU-T G.1070, but incorporates different enhancements, allowing a much better estimation of the perceptual MOS values, especially in low bit rate ranges. The error obtained with the proposed model, regarding to the ITU models, is between the ITU algorithms error margins, according to the subjective tests developed by the VQEG. Studies were made for more than 1500 processed video clips, coded in MPEG-2 and H.264/AVC, in bit rate ranges from 50 kb/s to 12 Mb/s, in SD, VGA, CIF and QCIF display formats.     

Asymmetrical principal component analysis for video coding

Principal component analysis (PCA) can be used to encode video sequences at extremely low bit rates, e.g. 34.6 dB (PSNR) at 4.2 kbit/s. The same eigenvectors are used for encoding and decoding for this coding. Introduced is a coding scheme where eigenvectors for only part of the video frames are used for encoding but the eigenvectors for the entire frame are used for decoding. This is called asymmetric PCA coding. This reduces the complexity of encoding by ap5 times and at the same time increases the reconstruction quality for the facial part of the video with 0.4 dB (PSNR)..