Quadratic Volterra filters and wavelet thresholding: two new approaches for noise reduction in images degraded by multiplicative signal-dependent noise

Olivier Delage; C. Thao Le; B. Savale; Henri H. Arsenault

doi:10.1117/12.279569

30 October 1997 Quadratic Volterra filters and wavelet thresholding: two new approaches for noise reduction in images degraded by multiplicative signal-dependent noise

Olivier Delage, C. Thao Le, B. Savale, Henri H. Arsenault

Author Affiliations +

Proceedings Volume 3164, Applications of Digital Image Processing XX; (1997) https://doi.org/10.1117/12.279569
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

In inertial confinement fusion experiments, images of neutron distributions provided by a large aperture imaging system are degraded by multiplicative and signal-dependent noise. In this case, it is difficult to separate the object's fluctuations from those of the noise. Wiener filtering is a well-known method which takes noise into account. Unfortunately, the Wiener filter is a low-pass filter which blurs the contours. The propose of this paper is to introduce two new approaches which restore most of the object's fluctuations. The first approach is a Wiener adaptive filtering method that consists of locally adjusting the value of the cutoff frequency. This adjustment is based on the basic properties of the human visual system where the visibility of noise can be reduced considerably in the neighborhood of a 'strong' contour. The contour detection is realized by means of a special class of quadratic Volterra filters. These filters are approximately equivalent to the product of a local mean estimator with a high pass filter. The second approach consists in applying a multiresolution decomposition of the raw image followed by a wavelet thresholding that changes for each resolution layer. Results and comparative evaluation of these two methods will also be presented.

Citation Download Citation

Olivier Delage, C. Thao Le, B. Savale, and Henri H. Arsenault "Quadratic Volterra filters and wavelet thresholding: two new approaches for noise reduction in images degraded by multiplicative signal-dependent noise", Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); https://doi.org/10.1117/12.279569

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Spatial resolution

Electronic filtering

Image filtering

Interference (communication)

Linear filtering

Wavelets

Edge detection

Show All Keywords

Keywords/Phrases

Search In:

Publication Years