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GPU decompression, Time-varying volume data, Vector quantization

She, Biao

Supervisor and department: Boulanger, PierreComputing Science

Examining committee member and department: Ray, Nilanjan Computing Science Noga, Michelle Radiology and Diagnostic Imaging

Department: Department of Computing Science

Specialization:

Date accepted: 2011-01-24T21:12:30Z

Graduation date: 2011-06

Degree: Master of Science

Degree level: Master's

Abstract: Real-time rendering of static volumetric data is generally known to be a memory and computationally intensive process. With the advance of graphic hardware, especially GPU, it is now possible to do this using desktop computers. However, with the evolution of real-time CT and MRI technologies, volumetric rendering is an even bigger challenge. The first one is how to reduce the data transmission between the main memory and the graphic memory. The second one is how to efficiently take advantage of the time redundancy which exists in the time-varying volumetric data. Most previous researches either focus on one problem or the other. In this thesis, we implemented a system which efficiently deals with both of the challenges.We proposed an optimized compression scheme that explores the time redundancy as well as space redundancy of time-varying volumetric data. The compressed data is then transmitted to graphic memory and directly rendered by GPU,so the data transfer between main memory and graphic memory is significantly reduced. With our implemented system, we successfully reduce more than half of the time of transferring the whole data directly. We also compare our proposed compression scheme with the one without exploiting time redundancy. The optimized compression scheme shows a reduce compression distortion over time. With usability, portability and extensibility in mind, the implemented system is also quite flexible.

Language: English

DOI: doi:10.7939-R3041M

Rights: License granted by Biao She bshe@cs.ualberta.ca on 2011-01-15T05:35:21Z GMT: Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.





Autor: She, Biao

Fuente: https://era.library.ualberta.ca/


Introducción



University of Alberta A System for Real-Time Rendering of Compressed Time-Varying Volume Data by Biao She A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science Department of Computing Science ©Biao She Spring 2011 Edmonton, Alberta Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only.
Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the authors prior written permission. Examining Committee Pierre Boulanger, Computing Science Michelle Noga, Radiology & Diagnostic Imaging Nilanjan Ray, Computing Science To my family For all your unconditional support. Abstract Real-time rendering of static volumetric data is generally known to be a memory and computationally intensive process.
With the advance of graphic hardware, especially GPU, it is now possible to do this using desktop computers.
However, with the evolution of real-time CT and MRI technologies, volumetric rendering is an even bigger challenge.
The first one is how to reduce the data transmission between the main memory and the graphic memory.
The second one is how to efficiently take advantage of the time redundancy which exists in the time-varying volumetric data.
Most previous researches either focus on one problem or the other.
In this thesis, we implemented a system which efficiently deals with both of the challenges. We proposed an optimized compression scheme that expl...





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