Exponential nonlinear Volterra filters for contrast sharpening in noisy images

Author

DeFigueiredo, Rui J P ; Matz, Sean C.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA

Volume

4

fYear

1996

fDate

7-10 May 1996

Firstpage

2263

Abstract

This paper presents a preliminary study of a new class of nonlinear (Volterra) filters which reduce the noise in an image while simultaneously enhancing the contrast. The design of these filters draws heavily from the theory of generalized Fock (GF) spaces of Volterra series. The structure of these filters is obtained by an orthogonal projection in a GF space under the data constraints. As a consequence, even though this structure embodies an infinite Volterra series, it is represented in a closed form as a linear combination of exponentials, the exponents of which are linear functions of the input image vector

Keywords

Gaussian noise; Volterra series; filtering theory; image enhancement; nonlinear filters; additive Gaussian noise; closed form structure; contrast enhancement; contrast sharpening; data constraints; exponential nonlinear Volterra filters; generalized Fock spaces; image noise reduction; infinite Volterra series; input image vector; linear functions; noisy images; orthogonal projection; Buildings; Computer vision; Filtering theory; Frequency; Laboratories; Machine intelligence; Noise reduction; Nonlinear filters; Poles and towers; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.545873

Filename

545873