Architectural considerations for a new generation of protocols
SIGCOMM '90 Proceedings of the ACM symposium on Communications architectures & protocols
Network-conscious GIF image transmission over the Internet
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue on high-performance protocol architectures
Network-Conscious Compressed Images over Wireless Networks
IDMS '98 Proceedings of the 5th International Workshop on Interactive Distributed Multimedia Systems and Telecommunication Services
NETCICATS: Network-Conscious Image Compression and Transmission System
MIS '98 Proceedings of the 4th International Workshop on Advances in Multimedia Information Systems
Robust Image Coding Using the Embedded Zerotree Wavelet Algorithm
DCC '96 Proceedings of the Conference on Data Compression
Intraframe Low Bit Rate Video Coding Robust to Packet Erasure
DCC '97 Proceedings of the Conference on Data Compression
Robust Wavelet Zerotree Image Compression with Fixed-Length Packetization
DCC '98 Proceedings of the Conference on Data Compression
Network-conscious image compression
Network-conscious image compression
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
The transport layer: tutorial and survey
ACM Computing Surveys (CSUR)
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Wavelet zerotree encoding has been proven to be an efficient way of compressing still images. Two well-known zerotree encoding algorithms, Embedded Zerotree Encoding (EZW) and Set Partitioning in Hierarchical Trees (SPIHT), provide excellent progressive display when images are transmitted over reliable networks. However, both algorithms are state-dependent and can perform poorly over unreliable networks.In this paper, we apply the concept of network-conscious image compression to the SPIHT wavelet zerotree-encoding algorithm, to improve its performance over unreliable networks. Experimental results confirm the utility of network-conscious image compression concept.