DocumentCode :
302887
Title :
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
Link To Document :
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