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Scalable low complexity image coder for remote volume visualization
Author(s) -
Hariharan G. Lalgudi,
Michael W. Marcellin,
Ali Bilgin,
Mariappan S. Nadar
Publication year - 2008
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.794430
Subject(s) - computer science , scalability , frame rate , volume rendering , visualization , rendering (computer graphics) , volume (thermodynamics) , bandwidth (computing) , workstation , data compression , throughput , real time computing , computer graphics (images) , computer vision , artificial intelligence , computer network , operating system , physics , quantum mechanics , wireless
Remote visualization of volumetric data has gained importance over the past few years in order to realize the full potential of tele-radiology. Volume rendering is a computationally intensive process, often requiring hardware acceleration to achieve real time visualization. Hence a remote visualization model that is well-suited for high speed networks would be to transmit rendered images from the server (with dedicated hardware) based on view point requests from clients. In this regard, a compression scheme for the rendered images is vital for efficient utilization of the server-client bandwidth. Also, the complexity of the decompressor should be considered so that a low end client workstation can decode images at the desired frame rate. We present a scalable low complexity image coder that has good compression efficiency and high throughput.

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