Quality Enhancement and Relation-Aware Exploration pipeline for Volume Visualization

PhD Thesis Proposal Defence


Title: "Quality Enhancement and Relation-Aware Exploration pipeline for Volume 
Visualization"

by

Mr. Ming-Yuen Chan


Abstract:

With the advance of data acquisition methods, various kinds of high quality 
volumetric datasets are now available for medical and scientific purposes. Due 
to the explosive increase in size and complexity of the data, the analysis 
tasks involved pose difficult problems. Volume visualization provides an 
effective solution which aims at delivering insights of the underlying details 
or concepts by the means of computer graphics for creating useful views on the 
data. In fact, effective visualization requires the support of intuitive and 
interactive exploration techniques as well as proper rendering and presentation 
of the data in order to facilitate the users in acquiring insights and useful 
information from the volumes. This proposal focuses on the improvement of the 
rendered image quality and the exploration pipeline to facilitate the 
visualization process.

In this proposal, we first present two exploration techniques for visualizing 
volumetric data. Instead of performing tedious manipulation on the volumes, we 
suggest a quality-driven camera path planning method and a relation-aware 
visualization pipeline to allow semi-automatic exploration of volumes. Volume 
features and high-level spatial relations are considered to determine the 
proper views on the volumes and our objective is to reveal this important 
information using the proposed visualization techniques. In the second part, 
the issues of rendered image quality are discussed and we propose two image 
quality enhancement approaches to ensure that the features in the volume are 
faithfully presented in the rendered images and correct perception of the 
volumes is obtained by viewers. An adaptive enhancement framework is also 
proposed to adjust the rendering parameters for obtaining optimal rendered 
images. To demonstrate the effectiveness of our solutions, experiments are 
conducted on different kinds of datasets and the results are evaluated and 
discussed.


Date:     		Monday, 25 May 2009

Time:                   4:00pm-6:00pm

Venue:                  Room 3405
 			lifts 17-18

Committee Members:      Dr. Huamin Qu (Supervisor)
 			Prof. Long Quan (Chairperson)
 			Dr. Chiew-Lan Tai
 			Prof. Dit-Yan Yeung


**** ALL are Welcome ****