
Proceedings Paper
Automatic network-adaptive ultra-low-bit-rate video codingFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper presents a software-only, real-time video coder/decoder (codec) for use with low-bandwidth channels where the bandwidth is unknown or varies with time. The codec incorporates a modified JPEG2000 core and interframe predictive coding, and can operate with network bandwidths of less than 1 kbits/second. The encoder and decoder establish two virtual connections over a single IP-based communications link. The first connection is UDP/IP guaranteed throughput, which is used to transmit the compressed video stream in real time, while the second is TCP/IP guaranteed delivery, which is used for two-way control and compression parameter updating. The TCP/IP link serves as a virtual feedback channel and enables the decoder to instruct the encoder to throttle back the transmission bit rate in response to the measured packet loss ratio. It also enables either side to initiate on-the-fly parameter updates such as bit rate, frame rate, frame size, and correlation parameter, among others. The codec also incorporates frame-rate throttling whereby the number of frames decoded is adjusted based upon the available processing resources. Thus, the proposed codec is capable of automatically adjusting the transmission bit rate and decoding frame rate to adapt to any network scenario. Video coding results for a variety of network bandwidths and configurations are presented to illustrate the vast capabilities of the proposed video coding system.
Paper Details
Date Published: 12 May 2006
PDF: 10 pages
Proc. SPIE 6246, Visual Information Processing XV, 624606 (12 May 2006); doi: 10.1117/12.665069
Published in SPIE Proceedings Vol. 6246:
Visual Information Processing XV
Zia-ur Rahman; Stephen E. Reichenbach; Mark A. Neifeld, Editor(s)
PDF: 10 pages
Proc. SPIE 6246, Visual Information Processing XV, 624606 (12 May 2006); doi: 10.1117/12.665069
Show Author Affiliations
Wei-Jung Chien, Arizona State Univ. (United States)
Tuyet-Trang Lam, Arizona State Univ. (United States)
Tuyet-Trang Lam, Arizona State Univ. (United States)
Glen P. Abousleman, General Dynamics C4 Systems (United States)
Lina J. Karam, Arizona State Univ. (United States)
Lina J. Karam, Arizona State Univ. (United States)
Published in SPIE Proceedings Vol. 6246:
Visual Information Processing XV
Zia-ur Rahman; Stephen E. Reichenbach; Mark A. Neifeld, Editor(s)
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