JOURNAL ARTICLE

<title>Techniques for resilient transmission of JPEG video streams</title>

Edward J. PosnakS. P. GallindoAdrian StephensHarrick M. Vin

Year: 1995 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2417 Pages: 243-252   Publisher: SPIE

Abstract

In this paper, we develop a transmission system, referred to as Dual Stream JPEG (DSJ), that improves the resiliency of JPEG video streams by unifying layered encoding with image scrambling techniques. Whereas layered encoding techniques naturally provide resiliency to isolated loss of low priority image data, scrambling techniques make is possible to distribute burst losses throughout the image. In DSJ, this unification is instantiated by employing the discrete cosine transform (DCT) to convert each 8 X 8 pixel block of an image into frequency domain, partitioning the resultant locks into high-priority DC coefficients and low-priority AC coefficients, and the scrambling the transmission of encoded blocks of AC coefficients. Furthermore, DSJ defines an adaptation layer that implements efficient error detection and recovery by including the sequence number and offset (relative to the beginning of the cell payload) of blocks carried in each cell. We have evaluated the performance of DSJ through extensive simulations. We present and analyze our results.

Keywords:
Scrambling Discrete cosine transform Computer science Payload (computing) Bitstream Pixel Transmission (telecommunications) Encoding (memory) Algorithm JPEG Real-time computing Data compression Image (mathematics) Computer hardware Artificial intelligence Computer network Telecommunications Decoding methods Network packet

Metrics

15
Cited By
1.41
FWCI (Field Weighted Citation Impact)
9
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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