Over the last years, we have seen exciting improvements in video compression technology, due to the introduction of HEVC and royalty-free coding specifications such as VP9. The potential compression gains of HEVC over H.264/AVC have been demonstrated in different studies, and are usually based on the HM reference software. For VP9, substantial gains over H.264/AVC have been reported in some publications, whereas others reported less optimistic results. Differences in configurations between these publications make it more difficult to assess the true potential of VP9. Practical open-source encoder implementations such as x265 and libvpx (VP9) have matured, and are now showing high compression gains over x264. In this paper, we demonstrate the potential of these encoder imple- mentations, with settings optimized for non-real-time random access, as used in a video-on-demand encoding pipeline. We report results from a large-scale video codec comparison test, which includes x264, x265 and libvpx. A test set consisting of a variety of titles with varying spatio-temporal characteristics from our catalog is used, resulting in tens of millions of encoded frames, hence larger than test sets previously used in the literature. Re- sults are reported in terms of PSNR, SSIM, MS-SSIM, VIF and the recently introduced VMAF quality metric. BD-rate calculations show that using x265 and libvpx vs. x264 can lead to significant bitrate savings for the same quality. x265 outperforms libvpx in most cases, but the performance gap narrows (or even reverses) at the higher resolutions.
The visual Just-Noticeable-Difference (JND) metric is characterized by the detectable minimum amount of two visual stimuli. Conducting the subjective JND test is a labor-intensive task. In this work, we present a novel interactive method in performing the visual JND test on compressed image/video. JND has been used to enhance perceptual visual quality in the context of image/video compression. Given a set of coding parameters, a JND test is designed to determine the distinguishable quality level against a reference image/video, which is called the anchor. The JND metric can be used to save coding bitrates by exploiting the special characteristics of the human visual system. The proposed JND test is conducted using a binary-forced choice, which is often adopted to discriminate the difference in perception in a psychophysical experiment. The assessors are asked to compare coded image/video pairs and determine whether they are of the same quality or not. A bisection procedure is designed to find the JND locations so as to reduce the required number of comparisons over a wide range of bitrates. We will demonstrate the efficiency of the proposed JND test, report experimental results on the image and video JND tests.
KEYWORDS: Computer programming, Video, Video compression, Video coding, Data compression, Motion estimation, Error control coding, Quantization, Distortion, Cameras
In current interframe video compression systems, the encoder performs predictive coding to exploit the similarities of successive frames. The Wyner-Ziv Theorem on source coding with side information available only at the decoder suggests that an asymmetric video codec, where individual frames are encoded separately, but decoded
conditionally (given temporally adjacent frames) could achieve similar efficiency. We propose a transformdomain Wyner-Ziv coding scheme for motion video that uses intraframe encoding, but interframe decoding. In this system, the transform coefficients of a Wyner-Ziv frame are encoded independently using a scalar quantizer and turbo coder. The decoder uses previously reconstructed frames to generate side information to conditionally decode the Wyner-Ziv frames. Simulation results show significant gains above DCT-based intraframe coding and improvements over the pixel-domain Wyner-Ziv video coder.
We present a novel scheme for error-resilient digital video broadcasting,using the Wyner-Ziv coding paradigm. We apply the general framework of systematic lossy source-channel coding to generate a supplementary bitstream that can correct transmission errors in the decoded video waveform up to a certain residual distortion. The systematic portion consists of a conventional MPEG-coded bitstream, which is transmitted over the error-prone channel without forward error correction.The supplementary bitstream is a low rate representation of the transmitted video sequence generated using Wyner-Ziv encoding. We use the conventionally decoded error-concealed MPEG video sequence as side information to decode the Wyner-Ziv bits. The decoder combines the error-prone side information and the Wyner-Ziv description to yield an improved decoded video signal. Our results indicate that, over a large range of channel error
probabilities, this scheme yields superior video quality when compared with traditional forward error correction techniques employed in digital video broadcasting.
Conference Committee Involvement (7)
Applications of Digital Image Processing XLIV
1 August 2021 | San Diego, California, United States
Applications of Digital Image Processing XLIII
24 August 2020 | Online Only, California, United States
Applications of Digital Image Processing XLII
12 August 2019 | San Diego, California, United States
Applications of Digital Image Processing XLI
20 August 2018 | San Diego, California, United States
Applications of Digital Image Processing XL
7 August 2017 | San Diego, California, United States
Applications of Digital Image Processing XXXIX
29 August 2016 | San Diego, California, United States
Applications of Digital Image Processing XXXVIII
10 August 2015 | San Diego, California, United States
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