The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform
Luc Vandendorpe - One of the best experts on this subject based on the ideXlab platform.
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hierarchical transform and subband coding of Video Signals
Signal Processing-image Communication, 1992Co-Authors: Luc VandendorpeAbstract:The new coding scheme allows the coding of different resolution Video Signals. The coding is performed in a way that makes it possible to decode either the whole or only some parts of the transmitted format. Transform and subband coding methods are considered. Transform coding is described in the light of the multirate filter bank theory. Coding systems of increasing efficiency are studied. The case of pure intra coding is quite easy to handle. More efficient systems include a temporal predictor. Some emphasis is put on those systems and especially on motion compensated schemes. The method proposed in this paper is the coding of the subbands using for prediction only the information of the same subbands or of the bands of lower order in the previous decoded picture.
Marijan Herceg - One of the best experts on this subject based on the ideXlab platform.
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No-reference real-time Video transmission artifact detection for Video Signals
Journal of Real-Time Image Processing, 2020Co-Authors: Ivan Glavota, Mario Vranješ, Zvonimir Kaprocki, Marijan HercegAbstract:Video Signals are a very important part of multimedia applications. Due to limited network bandwidth, Video Signals are subjected to the compression process, which introduces different compression artifacts. During network transmission, additional artifacts are introduced in Video Signals due to random bit errors and packet loss (PL). Both mentioned artifact types degrade visual quality of the Video signal and thus, it has to be continuously monitored to ensure the required quality of service (QoS) provided to end users. An important component of the Video quality monitoring system deals with Video transmission artifact detection. In this paper, a no-reference (NR) pixel-based Video transmission artifact detection algorithm is proposed, called the packet loss area measure (PLAM) algorithm. When detecting Video transmission artifacts, the PLAM algorithm takes into account spatial and temporal information of a Video signal. The performance of the proposed PLAM algorithm has been compared to those of the three existing different PL detection algorithms on a broad set of significantly different Video Signals from two publicly available Video databases. One of these databases, called the Referent Packet Loss (RPL) database, has been created within this research and is presented in this paper. The algorithm performance testing results show that PLAM achieves high performance and overcomes other tested algorithms. Furthermore, the results show that the PLAM algorithm is very robust when detecting Video transmission artifacts in Video Signals of different contents, with distinct degradation levels and PL error-concealment methods used in decoder post-processing. Due to its low computational complexity, the PLAM algorithm is capable of processing Full HD and Ultra HD Video Signals with the frame rate up to 100 and 25 frames per second (fps), respectively, in real time, in the case when high-end CPU is used.
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Pixel-based statistical analysis of packet loss artifact features
2016 Zooming Innovation in Consumer Electronics International Conference (ZINC), 2016Co-Authors: Ivan Glavota, Mario Vranješ, Marijan Herceg, Ratko GrbićAbstract:Due to high requirements on network capacity during network transmission, Video Signals have to be compressed. Compression process and network transmission introduce different compression artifacts and packet loss (PL) artifacts in Video Signals, respectively. These artifacts degrade visual quality of Video signal and thus Video quality has to be continuously measured and monitored in order to assure the target quality of service. Regarding PL artifacts, decoder's post-processing algorithm tries to mitigate or completely remove the visual impairments caused by the PL. Consequently, depending on error concealment method, different types of PL artifacts may be formed. In this paper we made a categorization of PL artifacts. The pixel-based statistical analysis of each PL artifact type is performed. The results show that the interesting statistical features can be extracted for the particular PL type, which can be further exploited in PL artifact detection algorithms and Video quality evaluation algorithms.
Louis Joseph Kerofsky - One of the best experts on this subject based on the ideXlab platform.
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VCIP - High-performance resolution-scalable Video coding via all-phase motion-compensated prediction of wavelet coefficients
Visual Communications and Image Processing 2002, 2002Co-Authors: Louis Joseph KerofskyAbstract:How to develop a multi-resolution representation of Video Signals for both efficient and scalable coding? What are fundamental advantages and limitations of a resolution scalable Video coder? How to make use of the scalability features of a Video codec to compromise other requirements (e.g. delay)? These are the central issues we address in this paper. We first demonstrate the importance of resolving the phase uncertainty on the efficiency of motion-compensated prediction (MCP) in the wavelet domain. Improved understanding of the relationship between phase associated with any wavelet transform (WT) and motion accuracy of MCP motivates us to develop a novel multi-resolution representation for Video Signals. The salient feature of our new representation is that MCP can be performed both effectively and independently at different resolutions. We apply previous theoretical results on fractional-pel MCP to analyze the sacrifice of coding efficiency due to the resolution scalability constraint. We also investigate the issue of delay in Video coding and propose a framework of trading delay with spatial resolution. A Video decoder can display a low-resolution frame with low delay first and then gracefully enhance the frame resolution as the delay increases. The low-delay resolution-scalable MCP-WT coder built upon our new wavelet-based multi-resolution representation of Video Signals has achieved significant Rate-Distortion improvements over previously-reported scalable coders in the literature and even outperforms non-scalable MPEG-2 coder by 1-2dB at the bit rate of 2-9Mbps.
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high performance resolution scalable Video coding via all phase motion compensated prediction of wavelet coefficients
Visual Communications and Image Processing, 2002Co-Authors: Louis Joseph KerofskyAbstract:How to develop a multi-resolution representation of Video Signals for both efficient and scalable coding? What are fundamental advantages and limitations of a resolution scalable Video coder? How to make use of the scalability features of a Video codec to compromise other requirements (e.g. delay)? These are the central issues we address in this paper. We first demonstrate the importance of resolving the phase uncertainty on the efficiency of motion-compensated prediction (MCP) in the wavelet domain. Improved understanding of the relationship between phase associated with any wavelet transform (WT) and motion accuracy of MCP motivates us to develop a novel multi-resolution representation for Video Signals. The salient feature of our new representation is that MCP can be performed both effectively and independently at different resolutions. We apply previous theoretical results on fractional-pel MCP to analyze the sacrifice of coding efficiency due to the resolution scalability constraint. We also investigate the issue of delay in Video coding and propose a framework of trading delay with spatial resolution. A Video decoder can display a low-resolution frame with low delay first and then gracefully enhance the frame resolution as the delay increases. The low-delay resolution-scalable MCP-WT coder built upon our new wavelet-based multi-resolution representation of Video Signals has achieved significant Rate-Distortion improvements over previously-reported scalable coders in the literature and even outperforms non-scalable MPEG-2 coder by 1-2dB at the bit rate of 2-9Mbps.
Shigenobu Shinohara - One of the best experts on this subject based on the ideXlab platform.
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Optical fiber transmission of multi-channel FM audio and Video Signals
IEEE Transactions on Consumer Electronics, 1993Co-Authors: N.a. Rabou, Hirofumi Yoshida, Hirotaka Ikeda, Shigenobu ShinoharaAbstract:An optical-fiber transmission system with a bandwidth of greater than 100 MHz for transmitting multichannel FM audio and Video Signals is described. This system for distributing FM audio and Video Signals on up to five channels to the respective receiver was constructed using a high-speed LED (light-emitting diode) and a wideband amplifier. The differential gain and differential phase were less than 2% and 3 degrees , respectively, and the SNR was 56 dB. The proposed system will be used for high-quality, high reliability distribution of multiple TV channels instead of the coaxial cable distribution systems. >
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OPTICAL FIBER TRANSMISSION OF MULTX- CHANNEL FM AUDIO AND Video Signals
1993Co-Authors: N.a. Rabou, Hirofumi Yoshida, Hiroaki Ikeda, Shigenobu ShinoharaAbstract:This paper describes an optical fiber transmission system with a bandwidth of greater than 100 MEiz to transmit multichannel FM audio and Video Signals through an optical fiber. The were less than 2% and respectively. and the SNR was
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Optical fiber transmission of SWFM signal for addressed audio and Video Signals
Proceedings of 36th Midwest Symposium on Circuits and Systems, 1Co-Authors: Hiroaki Ikeda, Hirofumi Yoshida, Shigenobu ShinoharaAbstract:Described is an addressed audio and Video signal transmission system in which audio and Video Signals together with their address consisting of 8 frequencies can simultaneously be sent from the sender to the designated receivers through the optical fibers. The received audio signal covered the frequency range of 10 Hz to 20 kHz with a distortion factor of less than 0.5% and with an SNR of 60 dB (62 dB without addresses). The received Video signal covered the frequency range of 100 Hz to 4.2 MHz with a DG of less than 5% and with a DP of less than 5 degrees. >
Keith Jack - One of the best experts on this subject based on the ideXlab platform.
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Chapter 3 – Video Signals
Digital Video and DSP, 2008Co-Authors: Keith JackAbstract:Publisher Summary This chapter provides an overview of the common Video signal formats and their timing. It gives definitions of several terms related to Video Signals including SDTV (Standard Definition Television), NTSC (National Television System Committee), HDTV (High-Definition Television), active Video, aspect ratio, and color bars. Digital component Video is digital Video that uses three separate color components, such as R'G'B' or YCbCr. In digital component Video, the Video Signals are in digital form (YCbCr or R'G'B'), being encoded to composite NTSC, PAL, or SECAM only when it is necessary for broadcasting or recording purposes. 480i and 480p systems include interlaced analog composite Video, progressive analog component Video, interlaced digital component Video, and progressive digital component Video at 480 active scan lines per frame. 576i and 576p systems include analog composite Video, interlaced analog component Video, progressive analog component Video, interlaced digital component Video, and progressive digital component Video at 576 active scan lines per frame. 720p systems include progressive analog component Video and progressive digital component Video at 720 active scan lines per frame. 1080i and 1080p systems include interlaced analog component Video, progressive analog component Video, interlaced digital component Video, and progressive digital component Video at 1080 active scan lines per frame.
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Chapter 4 – Video Signals Overview
Video Demystified, 2007Co-Authors: Keith JackAbstract:Publisher Summary This chapter provides an overview of the common Video signal formats and their timing. Video formats discussed include 480i, 480p, 576i, 576p, 720p, 1080i, and 1080p. In digital component Video, the Video Signals are in digital form (YCbCr or R’G’B’), being encoded to composite NTSC, PAL, or SECAM only when it is necessary for broadcasting or recording purposes. NTSC and PAL are analog composite Video Signals that carry all timing and color information within a single signal. Analog component Signals are comprised of three Signals—analog, R’G’B’, or YPbPr. Referred to as 480i, the frame rate is usually 29.97 Hz (30/1.001) for compatibility with NTSC timing. The analog interface uses 525 lines per frame, with active Video present on lines 23–262 and 286–525.
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Video Signals Overview
Video Demystified, 2005Co-Authors: Keith JackAbstract:Publisher Summary The chapter reviews the Video timing, and the analog and digital representations of various Video formats, including 480i, 480p, 576i, 576p, 720p, 1080i, and 1080p. They come in a wide variety of options, number of scan lines, interlaced vs. progressive, analog vs. digital, and so on. The chapter provides an overview of the common Video signal formats and their timing. In a digital component Video, the Video Signals are in digital form (YCbCr or R'G'B'), being encoded to composite National Television System Committee (NTSC), Phase Alternation Line (PAL), or Sequential Color with Memory (SECAM) only when it is necessary for broadcasting or recording purposes. For 8-bit systems, the values of 00H and FFH are reserved for timing information. For 10-bit systems, the values of 000H-003H and 3FCH-3FFH are reserved for timing information, to maintain compatibility with 8-bit systems.
