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报告题目:Total variation (TV) based mathematical model for wavelet inpainting.

报告时间:2015年8月2日(周日)上午9:30

报告地点:北校区西大楼Ⅲ-405

报 告 人:Haomin Zhou 教授(佐治亚理工学院)

报告摘要:

Wavelet inpainting aims at repairing lost or damaged wavelet coefficients during transmission or storage processes. The problem faces several major challengesincluding spatially inhomogeneous damages and no clear region to work on in the imagedomain. In this talk, we discuss the total variation (TV) models to restore the image with desirable geometric properties. We designed a primal-dual hybridgradient (PDHG) algorithm, similar method has been successfully applied to a number of total variation (TV) based image reconstruction problems, for fast numerical solutions. In particular, we propose an approximated PDHG algorithm to tackle the non-orthogonality of Daubechies 7-9 wavelet which is widely used in practice. We show that this approximated version essentially alters the gradient descent direction in the original PDHG algorithm, but eliminatesits orthogonality restriction and retains low computation complexity.This work is jointly with Xiaojing Ye (Georgia State).

报告人简介:

Haomin Zhou教授在1996年获得The Chinese University of Hong Kong,数学专业硕士学位,2000年获美国University of California, Los Angles, USA,应用数学专业博士学位,现就职于Georgia Institute of Technology,研究方向为Numerical analysis and scientific computing,Wavelets and PDE based image processing,Random dynamical systems等,研究课题具有极大的创新性、前沿性和必要性。Haomin Zhou教授长期对光学成像领域的逆问题和数学建模问题进行研究,尤其对光学成像建模有着自己独到的见解。

近年来,已在国际高水平期刊与会议发表论文50余篇,包括Journal of Mathematical Imaging and Vision、the International Journal on Biomedical Imaging、Optics Letters、IEEE Transcation on Image Processing等高水平期刊(影响因子超过3)数篇,作国际特约报告38次。曾获得多项奖学金及荣誉,包括Honorable Mention in Householder Award XI, Guang Hua awrad和Jiu Zhang award等。同时获得包括NSF Grant, NSF Faculty Early Career Development (CAREER) Award等多项美国自然科学基金给予的资助和奖项。

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