Neural network implementation of the SMSE filter for imaging processing

Edwin P. K. Wong; Ling Guan; Stuart W. Perry

doi:10.1117/12.234640

5 March 1996 Neural network implementation of the SMSE filter for imaging processing

Edwin P. K. Wong, Ling Guan, Stuart W. Perry

Proceedings Volume 2661, Real-Time Imaging; (1996) https://doi.org/10.1117/12.234640
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

Abstract

This paper presents an implementation and enhancement of the SMSE (scaled mean square error) filter, using a Hopfield neural network based algorithm. We show the development of the original SMSE filter from the MMSE (minimum mean square error) filter and the PMSE (parametric mean square error) filter, both of which suffer from the oversmooth phenomena. The SMSE filter is more efficient than the PMSE filter in terms of noise removal as it does not take into account all the correlation factors used for image restoration. An adaptive SMSE filter is also presented. The adaptive SMSE filter uses a mask operation technique. A user- defined mask is moved across the image and the filtering parameters are computed based on the local image statistics of the region below the mask. The original and adaptive SMSE filters are implemented using a Hopfield neural network based algorithm. A number of experiments were performed to test the filter characteristics.

Citation Download Citation

Edwin P. K. Wong, Ling Guan, and Stuart W. Perry "Neural network implementation of the SMSE filter for imaging processing", Proc. SPIE 2661, Real-Time Imaging, (5 March 1996); https://doi.org/10.1117/12.234640

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