Analysis on finite length solubility of linear symmetric real blurring kernel and relevant judging algorithm

Author

Bing Hao ; Tingzhi Shen ; Nan Yang

Author_Institution

Beijing Inst. of Technol. Sch. of Inf. Sci. & Technol., Beijing

fYear

2008

Firstpage

937

Lastpage

941

Abstract

The paper mainly discusses the finite length solubility of 1-dimension and 2-dimension linear symmetric real blurring kernel function (LSRBKF) applied in signal and image processing. The necessary and sufficient conditions of the finite solubility are proposed and proved then. Given the known LSRBKF, two simple and practicable algorithms for judging whether the finite anti blurring can realize are developed, and positive experiment results are obtained through simulation.

Keywords

image restoration; polynomials; anti blurring; finite length solubility analysis; image restoration; linear symmetric real image blurring kernel; polynomial; relevant judging algorithm; Algorithm design and analysis; Image analysis; Kernel; Least squares approximation; Least squares methods; Measurement standards; Paper technology; Signal processing; Signal processing algorithms; Sufficient conditions; finite solubility; judging algorithm; linear symmetric real blurring kernel function; simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2008. ICSP 2008. 9th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2178-7

Electronic_ISBN

978-1-4244-2179-4

Type

conf

DOI

10.1109/ICOSP.2008.4697281

Filename

4697281