A robust regularized restoration algorithm based on Topkis-Veinott optimization method

Daan Zhu; M. Razaz; R. Lee

doi:10.1109/ICPR.2004.1333870

A robust regularized restoration algorithm based on Topkis-Veinott optimization method

Daan Zhu, M. Razaz, R. Lee

School of Computing Sciences

Research output: Contribution to conference › Other

Abstract

We present a robust iterative algorithm for restoration of blurred and noisy images. The restoration model is first regularised and then solved iteratively. An optimal regularisation parameter is estimated using the Topkis-Veinott gradient method. This restoration algorithm is compared with other competitive restoration algorithms in the literature. Experimental results are presented to demonstrate the comparative important features of our algorithm, namely, robustness in the presence of noise and high quality restoration results.

Original language	English
Pages	705-708
Number of pages	4
DOIs	https://doi.org/10.1109/ICPR.2004.1333870
Publication status	Published - 2004
Event	17th International Conference on Pattern Recognition - Cambridge, United Kingdom Duration: 23 Aug 2004 → 26 Aug 2004

Conference

Conference	17th International Conference on Pattern Recognition
Abbreviated title	ICPR-2004
Country/Territory	United Kingdom
City	Cambridge
Period	23/08/04 → 26/08/04

Access to Document

10.1109/ICPR.2004.1333870

Cite this

@conference{39799f990b7a42c3acda14a1fcb7b37c,

title = "A robust regularized restoration algorithm based on Topkis-Veinott optimization method",

abstract = "We present a robust iterative algorithm for restoration of blurred and noisy images. The restoration model is first regularised and then solved iteratively. An optimal regularisation parameter is estimated using the Topkis-Veinott gradient method. This restoration algorithm is compared with other competitive restoration algorithms in the literature. Experimental results are presented to demonstrate the comparative important features of our algorithm, namely, robustness in the presence of noise and high quality restoration results.",

author = "Daan Zhu and M. Razaz and R. Lee",

year = "2004",

doi = "10.1109/ICPR.2004.1333870",

language = "English",

pages = "705--708",

note = "17th International Conference on Pattern Recognition, ICPR-2004 ; Conference date: 23-08-2004 Through 26-08-2004",

}

TY - CONF

T1 - A robust regularized restoration algorithm based on Topkis-Veinott optimization method

AU - Zhu, Daan

AU - Razaz, M.

AU - Lee, R.

PY - 2004

Y1 - 2004

N2 - We present a robust iterative algorithm for restoration of blurred and noisy images. The restoration model is first regularised and then solved iteratively. An optimal regularisation parameter is estimated using the Topkis-Veinott gradient method. This restoration algorithm is compared with other competitive restoration algorithms in the literature. Experimental results are presented to demonstrate the comparative important features of our algorithm, namely, robustness in the presence of noise and high quality restoration results.

AB - We present a robust iterative algorithm for restoration of blurred and noisy images. The restoration model is first regularised and then solved iteratively. An optimal regularisation parameter is estimated using the Topkis-Veinott gradient method. This restoration algorithm is compared with other competitive restoration algorithms in the literature. Experimental results are presented to demonstrate the comparative important features of our algorithm, namely, robustness in the presence of noise and high quality restoration results.

U2 - 10.1109/ICPR.2004.1333870

DO - 10.1109/ICPR.2004.1333870

M3 - Other

SP - 705

EP - 708

T2 - 17th International Conference on Pattern Recognition

Y2 - 23 August 2004 through 26 August 2004

ER -