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Distributed video coding in wireless multimedia sensor network for multimedia broadcasting
Recently the development of Distributed Video Coding (DVC) has provided the promising theory
support to realize the infrastructure of Wireless Multimedia Sensor Network (WMSN), which composed of autonomous hardware for capturing and transmission of quality audio-visual content. The implementation of DVC in WMSN can better solve the problem of energy constraint of the sensor nodes due to the benefit of lower computational encoder in DVC. In this paper, a practical DVC scheme, pixel-domain Wyner-Ziv(PDWZ) video
coding, with slice structure and adaptive rate selection(ARS) is proposed to solve the certain problems when applying DVC into WMSN. Firstly, the proposed slice structure in PDWZ has extended the feasibility of PDWZ to work with any interleaver size used in Slepian-wolf turbo codec for heterogeneous applications. Meanwhile,
based on the slice structure, an adaptive code rate selection has been proposed aiming at reduce the system delay occurred in feedback request. The simulation results clearly showed the enhancement in R-D performance and perceptual quality. It also can be observed that system delay caused by frequent feedback is greatly reduced, which gives a promising support for WMSN with low latency and facilitates the QoS management
Lowpass Filtering of Rate-Distortion Functions for Quality Smoothing in Real-Time Video Communication
Digital Object Identifier 10.1109/TCSVT.2005.852417In variable-bit-rate (VBR) video coding, the video is pre-processed to collect sequence-level statistics, which are used
for global bit allocation in the actual encoding stage to obtain a smoothed video presentation quality. However, in real-time
video recording and network streaming, this type of two-pass encoding scheme is not allowed because the access to future frames and global statistics is not available. To address this issue, we introduce the concept of low-pass filtering of rate-distortion
(R-D) functions and develop a smoothed rate control (SRC) framework for real-time video recording and streaming. Theoretically, we prove that, using a geometric averaging filter,
the SRC algorithm is able to maintain a smoothed video presentation quality while achieving the target bit rate automatically.
We also analyze the buffer requirement of the SRC algorithm in real-time video streaming, and propose a scheme to seamlessly integrate robust buffer control into the SRC framework. The proposed SRC algorithm has very low computational complexity and implementation cost. Our extensive experimental results
demonstrate that the SRC algorithm significantly reduces the picture quality variation in the encoded video clips
Video Traffic Characteristics of Modern Encoding Standards: H.264/AVC with SVC and MVC Extensions and H.265/HEVC
abstract: Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC.View the article as published at https://www.hindawi.com/journals/tswj/2014/189481
Study of information transfer optimization for communication satellites
The results are presented of a study of source coding, modulation/channel coding, and systems techniques for application to teleconferencing over high data rate digital communication satellite links. Simultaneous transmission of video, voice, data, and/or graphics is possible in various teleconferencing modes and one-way, two-way, and broadcast modes are considered. A satellite channel model including filters, limiter, a TWT, detectors, and an optimized equalizer is treated in detail. A complete analysis is presented for one set of system assumptions which exclude nonlinear gain and phase distortion in the TWT. Modulation, demodulation, and channel coding are considered, based on an additive white Gaussian noise channel model which is an idealization of an equalized channel. Source coding with emphasis on video data compression is reviewed, and the experimental facility utilized to test promising techniques is fully described
Implementation issues in source coding
An edge preserving image coding scheme which can be operated in both a lossy and a lossless manner was developed. The technique is an extension of the lossless encoding algorithm developed for the Mars observer spectral data. It can also be viewed as a modification of the DPCM algorithm. A packet video simulator was also developed from an existing modified packet network simulator. The coding scheme for this system is a modification of the mixture block coding (MBC) scheme described in the last report. Coding algorithms for packet video were also investigated
Perceptually-Driven Video Coding with the Daala Video Codec
The Daala project is a royalty-free video codec that attempts to compete with
the best patent-encumbered codecs. Part of our strategy is to replace core
tools of traditional video codecs with alternative approaches, many of them
designed to take perceptual aspects into account, rather than optimizing for
simple metrics like PSNR. This paper documents some of our experiences with
these tools, which ones worked and which did not. We evaluate which tools are
easy to integrate into a more traditional codec design, and show results in the
context of the codec being developed by the Alliance for Open Media.Comment: 19 pages, Proceedings of SPIE Workshop on Applications of Digital
Image Processing (ADIP), 201
GRACE: Loss-Resilient Real-Time Video through Neural Codecs
In real-time video communication, retransmitting lost packets over
high-latency networks is not viable due to strict latency requirements. To
counter packet losses without retransmission, two primary strategies are
employed -- encoder-based forward error correction (FEC) and decoder-based
error concealment. The former encodes data with redundancy before transmission,
yet determining the optimal redundancy level in advance proves challenging. The
latter reconstructs video from partially received frames, but dividing a frame
into independently coded partitions inherently compromises compression
efficiency, and the lost information cannot be effectively recovered by the
decoder without adapting the encoder.
We present a loss-resilient real-time video system called GRACE, which
preserves the user's quality of experience (QoE) across a wide range of packet
losses through a new neural video codec. Central to GRACE's enhanced loss
resilience is its joint training of the neural encoder and decoder under a
spectrum of simulated packet losses. In lossless scenarios, GRACE achieves
video quality on par with conventional codecs (e.g., H.265). As the loss rate
escalates, GRACE exhibits a more graceful, less pronounced decline in quality,
consistently outperforming other loss-resilient schemes. Through extensive
evaluation on various videos and real network traces, we demonstrate that GRACE
reduces undecodable frames by 95% and stall duration by 90% compared with FEC,
while markedly boosting video quality over error concealment methods. In a user
study with 240 crowdsourced participants and 960 subjective ratings, GRACE
registers a 38% higher mean opinion score (MOS) than other baselines
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