Effective erasure codes for reliable computer communication protocols
ACM SIGCOMM Computer Communication Review
Pattern matching algorithms
Progressive Image Coding on Noisy Channels
DCC '97 Proceedings of the Conference on Data Compression
Graceful Degradation over Packet Erasure Channels through Forward Error Correction
DCC '99 Proceedings of the Conference on Data Compression
Joint Source-Channel Coding for Progressive Transmission of Embedded Source Coders
DCC '99 Proceedings of the Conference on Data Compression
Wireless Image Transmission Using Multiple-Description Based Concatenated Codes
DCC '00 Proceedings of the Conference on Data Compression
Priority encoding transmission
IEEE Transactions on Information Theory - Part 1
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
EURASIP Journal on Applied Signal Processing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
IEEE Transactions on Image Processing
Embedded packetization framework for layered multiple description coding
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part III
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In this extended abstract we present a family of new algorithms for rate-fidelity optimal packetization of scalable source bit stream with uneven error protection. In the most general setting where no assumption is made on the probability function of pack et loss or on the rate-fidelity function of the scalable code stream, one of our algorithms can find the globally optimal solution to the problem in time, compared to a previously claimed complexity, whereN is the number of packets and L is the packet payload size. The time complexity can be reduced to if the rate-fidelity function of the input is convex and under the reasonable assumption that the probability function of packet loss is monotonically decreasing.In the convex case the algorithm of Mohr et al. [6] has complexity . Furthermore,our algorithm for the convex case can be modified to find an approximation solution for the general case that is better than the results of other algorithms in the prior literature. All of our algorithms do away with the expediency of fractional redundancy allocation, a limitation of some existing algorithms. To our best knowledge this work offers for the first time globally optimal solutions to the important problem of optimal UEP packetization.