Blind image deconvolution using a banded matrix method

被引：6
|
作者：
Danelakis, Antonios [1 ]
Mitrouli, Marilena [2 ]
Triantafyllou, Dimitrios [3 ]
机构：
[1] Univ Athens, Dept Informat & Telecommun, Athens 15784, Greece
[2] Univ Athens, Dept Math, Athens 15784, Greece
[3] Hellen Army Acad, Dept Mil Sci, Sect Math & Engn Sci, Vari, Greece
来源：
NUMERICAL ALGORITHMS | 2013年 / 64卷 / 01期
关键词：
Blind image deconvolution; Blurring function; Univariate polynomial; Greatest Common Divisor; Banded matrix; Convolution; ALGORITHM; REGULARIZATION;
D O I：
10.1007/s11075-012-9654-y
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper we study the blind image deconvolution problem in the presence of noise and measurement errors. We use a stable banded matrix based approach in order to robustly compute the greatest common divisor of two univariate polynomials and we introduce the notion of approximate greatest common divisor to encapsulate the above approach, for blind image restoration. Our method is analyzed concerning its stability and complexity resulting to useful conclusions. It is proved that our approach has better complexity than the other known greatest common divisor based blind image deconvolution techniques. Examples illustrating our procedures are given.
引用
收藏
页码：43 / 72
页数：30
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