Abstract-A no-reference (NR) video quality assessment (VQA) method is presented for videos distorted by H.264/Advanced Video Coding (AVC) and MPEG-2. The assessment is performed without access to the bitstream. Instead, we analyze and estimate coefficients based on decoded pixels. The approach involves distinguishing between the two types of videos, estimating the level of quantization used in the I-frames, and exploiting this information to assess the video quality. To do this for H.264/AVC, the distribution of the discrete cosine transform-coefficients after intra-prediction and deblocking are modeled. To obtain VQA features for H.264/AVC, we propose a novel estimation method of the quantization in H.264/AVC videos without bitstream access, which can also be used for peak signal-to-noise ratio estimation. The results from the MPEG-2 and H.264/AVC analysis are mapped to a perceptual measure of video quality by support vector regression. For validation purposes, the proposed method was tested on two databases. In both cases, a good performance compared with state of the art full, reduced, and NR VQA algorithms was achieved. Index Terms-H.264/Advanced Video Coding (AVC), no-reference (NR), peak signal-to-noise ratio (PSNR) estimation, pixel-based (PB), video codec analysis, video quality assessment (VQA).
Similar principles were proposed in REF by using features extracted from specific codecs (MPEG or H.264/AVC), the analysis of DCT coefficients, the estimation of the quantization level used in the I-frames to measure quality of videos distorted by only the compression process.
No-Reference Video Quality Assessment Using Codec Analysis
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Computer Science