Robust drift-free bit-rate preserving H.264 watermarking

International audienceThis paper presents a novel method for open-loop watermarking of H.264/AVC bitstreams. Existing watermarking algorithms designed for previous encoders, such as MPEG-2 cannot be directly applied to H.264/AVC, as H.264/AVC implements numerous new features that were not considered in previous coders. In contrast to previous watermarking techniques for H.264/AVC bitstreams, which embed the information after the reconstruction loop and perform drift compensation, we propose a completely new intra-drift-free watermarking algorithm. The major design goals of this novel H.264/AVC watermarking algorithm are runtime-efficiency, high perceptual quality, (almost) no bit-rate increase and robustness to re-compression. The watermark is extremely runtime-efficiently embedded in the compressed domain after the reconstruction loop, i.e., all prediction results are reused. Nevertheless, intra-drift is avoided, as the watermark is embedded in such a way that the pixels used for the prediction are kept unchanged. Thus, there is no drift as the pixels being used in the intra-prediction process of H.264/AVC are not modified. For watermark detection, we use a two-stage cross-correlation. Our simulation results confirm that the proposed technique is robust against re-encoding and shows a negligible impact on both the bit-rate and the visual quality

Complexity adaptation in video encoders for power limited platforms

With the emergence of video services on power limited platforms, it is necessary to consider both performance-centric and constraint-centric signal processing techniques. Traditionally, video applications have a bandwidth or computational resources constraint or both. The recent H.264/AVC video compression standard offers significantly improved efficiency and flexibility compared to previous standards, which leads to less emphasis on bandwidth. However, its high computational complexity is a problem for codecs running on power limited plat- forms. Therefore, a technique that integrates both complexity and bandwidth issues in a single framework should be considered. In this thesis we investigate complexity adaptation of a video coder which focuses on managing computational complexity and provides significant complexity savings when applied to recent standards. It consists of three sub functions specially designed for reducing complexity and a framework for using these sub functions; Variable Block Size (VBS) partitioning, fast motion estimation, skip macroblock detection, and complexity adaptation framework. Firstly, the VBS partitioning algorithm based on the Walsh Hadamard Transform (WHT) is presented. The key idea is to segment regions of an image as edges or flat regions based on the fact that prediction errors are mainly affected by edges. Secondly, a fast motion estimation algorithm called Fast Walsh Boundary Search (FWBS) is presented on the VBS partitioned images. Its results outperform other commonly used fast algorithms. Thirdly, a skip macroblock detection algorithm is proposed for use prior to motion estimation by estimating the Discrete Cosine Transform (DCT) coefficients after quantisation. A new orthogonal transform called the S-transform is presented for predicting Integer DCT coefficients from Walsh Hadamard Transform coefficients. Complexity saving is achieved by deciding which macroblocks need to be processed and which can be skipped without processing. Simulation results show that the proposed algorithm achieves significant complexity savings with a negligible loss in rate-distortion performance. Finally, a complexity adaptation framework which combines all three techniques mentioned above is proposed for maximizing the perceptual quality of coded video on a complexity constrained platform

Escaping the complexity-bitrate-quality barriers of video encoders via deep perceptual optimization

We extend the concept of learnable video precoding (rate-aware neural-network processing prior to encoding) to deep perceptual optimization (DPO). Our framework comprises a pixel-to-pixel convolutional neural network that is trained based on the virtualization of core encoding blocks (block transform, quantization, block-based prediction) and multiple loss functions representing rate, distortion and visual quality of the virtual encoder. We evaluate our proposal with AVC/H.264 and AV1 under per-clip rate-quality optimization. The results show that DPO offers, on average, 14.2% bitrate reduction over AVC/H.264 and 12.5% bitrate reduction over AV1. Our framework is shown to improve both distortion- and perception-oriented metrics in a consistent manner, exhibiting only 3% outliers, which correspond to content with peculiar characteristics. Thus, DPO is shown to offer complexity-bitrate-quality tradeoffs that go beyond what conventional video encoders can offe

An Analysis of VP8, a new video codec for the web

Video is an increasingly ubiquitous part of our lives. Fast and efficient video codecs are necessary to satisfy the increasing demand for video on the web and mobile devices. However, open standards and patent grants are paramount to the adoption of video codecs across different platforms and browsers. Google On2 released VP8 in May 2010 to compete with H.264, the current standard of video codecs, complete with source code, specification and a perpetual patent grant. As the amount of video being created every day is growing rapidly, the decision of which codec to encode this video with is paramount; if a low quality codec or a restrictively licensed codec is used, the video recorded might be of little to no use. We sought to study VP8 and its quality versus its resource consumption compared to H.264 -- the most popular current video codec -- so that reader may make an informed decision for themselves or for their organizations about whether to use H.264 or VP8, or something else entirely. We examined VP8 in detail, compared its theoretical complexity to H.264 and measured the efficiency of its current implementation. VP8 shares many facets of its design with H.264 and other Discrete Cosine Transform (DCT) based video codecs. However, VP8 is both simpler and less feature rich than H.264, which may allow for rapid hardware and software implementations. As it was designed for the Internet and newer mobile devices, it contains fewer legacy features, such as interlacing, than H.264 supports. To perform quality measurements, the open source VP8 implementation libvpx was used. This is the reference implementation. For H.264, the open source H.264 encoder x264 was used. This encoder has very high performance, and is often rated at the top of its field in efficiency. The JM reference encoder was used to establish a baseline quality for H.264. Our findings indicate that VP8 performs very well at low bitrates, at resolutions at and below CIF. VP8 may be able to successfully displace H.264 Baseline in the mobile streaming video domain. It offers higher quality at a lower bitrate for low resolution images due to its high performing entropy coder and non-contiguous macroblock segmentation. At higher resolutions, VP8 still outperforms H.264 Baseline, but H.264 High profile leads. At HD resolution (720p and above), H.264 is significantly better than VP8 due to its superior motion estimation and adaptive coding. There is little significant difference between the intra-coding performance between H.264 and VP8. VP8\u27s in-loop deblocking filter outperforms H.264\u27s version. H.264\u27s inter-coding, with full support for B frames and weighting outperforms VP8\u27s alternate reference scheme, although this may improve in the future. On average, VP8\u27s feature set is less complex than H.264\u27s equivalents, which, along with its open source implementation, may spur development in the future. These findings indicate that VP8 has strong fundamentals when compared with H.264, but that it lacks optimization and maturity. It will likely improve as engineers optimize VP8\u27s reference implementation, or when a competing implementation is developed. We recommend several areas that the VP8 developers should focus on in the future

Adapting x264 to asynchronous video telephony for the Deaf

Deaf people want to communicate remotely with sign language. Sign language requires sufficient video quality to be intelligible. Internet-based real-time video tools do not provide that quality. Our approach is to use asynchronous transmission to maintain video quality. Unfortunately, this entails a corresponding increase in latency. To reduce latency as much as possible, we sought to adapt a synchronous video codec to an asynchronous video application. First we compared several video codecs with subjective and objective metrics. This paper describes the process by which we chose x264 and integrated it into a Deaf telephony video application, and experimented to configure x264 optimally for the asynchronous environment.Telkom, Cisco, THRIP, SANPADDepartment of HE and Training approved lis

Fast fallback watermark detection using perceptual hashes

Forensic watermarking is often used to enable the tracing of digital pirates that leak copyright-protected videos. However, existing watermarking methods have a limited robustness and may be vulnerable to targeted attacks. Our previous work proposed a fallback detection method that uses secondary watermarks rather than the primary watermarks embedded by existing methods. However, the previously proposed fallback method is slow and requires access to all watermarked videos. This paper proposes to make the fallback watermark detection method faster using perceptual hashes instead of uncompressed secondary watermark signals. These perceptual hashes can be calculated prior to detection, such that the actual detection process is sped up with a factor of approximately 26,000 to 92,000. In this way, the proposed method tackles the main criticism about practical usability of the slow fallback method. The fast detection comes at the cost of a modest decrease in robustness, although the fast fallback detection method can still outperform the existing primary watermark method. In conclusion, the proposed method enables fast and more robust detection of watermarks that were embedded by existing watermarking methods

A testbed of erasure coding on video streaming system over lossy networks

As one of the most challenging aspects of streaming video over lossy networks, the technology for controlling packet losses has attracted more and more attention. Erasure coding is one of the ideal choices to deal with this problem. In most cases, the researchers need an effective method or tool to validate the erasure codes used for dealing with different packet loss patterns. Although some previous work has been done on employing erasure codes in video streaming system, few actual buildups and experiments which involve implementation of erasure codes against real packet loss in streaming systems have been reported. In this paper, we focus on constructing a testbed that integrates loss pattern generation and erasure coding implementation into video streaming services over lossy networks. With this approach, we are able to assess the capability of erasure coding in packet loss control and compare the performances of the video streaming systems with and without erasure coding. As an example, we have implemented the Reed-Solomon (7, 5) code for protecting MPEG streaming data under random packet losses. Experiment results show that the replay quality can be improved significantly by using erasure coding in video streaming systems, and that the testbed can suggest appropriate erasure code parameters for different loss environments

Complexity management for video encoders.

Software implementation of block-based video coding standards has been used in a wide range of applications. In many cases, such as real-time multimedia systems or power-constrained systems, the coding performance of software-only video encoders and decoders is limited by computational complexity. This thesis presents research work to develop techniques to manage computational complexity of video encoders. These techniques aim to provide significant complexity saving as well as adaptively controlling the computational complexity. This thesis first investigates experimentally the most computationally intensive functions in a video encoder. Based on the results of profile tests, several functions are selected as candidates, on which complexity reduction algorithms will be performed. These functions include discrete cosine transform and related functions as well as motion estimation. Adaptive complexity-reduction algorithms are proposed for computationally expensive functions: discrete cosine transform and motion estimation functions respectively. It is shown that these algorithms can flexibly control the computational complexity of each function with negligible loss of video quality. The inherent characteristics of coded macroblocks are investigated through experimental tests and they are categorized into "skipped" and" unskipped" macroblocks based on two parameters. An innovative algorithm is developed to reduce the computational complexity by predicting "skipped" macroblock prior to encoding and not carrying out the coding process on these macroblocks. The approaches described in this thesis can not only achieve adaptive control of the computational complexity of a video encoder, but also can manage the trade-off between complexity and distortion. These proposed algorithms are evaluated in terms of complexity reduction performance, rate-distortion performance and subjective and objective visual quality by experimental testing.The advantages and disadvantages of each algorithm are discussed