Application of neural network to restoration of signals degraded by a stochastic, shift-variant impulse response function and additive noise

Mehmet Bilgen; Hsien-Sen Hung

doi:10.1117/12.48384

1 October 1991 Application of neural network to restoration of signals degraded by a stochastic, shift-variant impulse response function and additive noise

Mehmet Bilgen, Hsien-Sen Hung

Author Affiliations +

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48384
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

An artificial neural network is adopted for estimating discrete (sampled in time and quantized in amplitude) signals degraded by a stochastic, shift-variant impulse response (blur) function in the presence of noise. The signal restoration problem is formulated as a combinatorial optimization problem wherein a nonlinear cost function, termed stochastic constrained restoration error energy, is to be minimized. By matching the cost function with the energy function of the associated neural network, the interconnection strengths and bias inputs of the neural network are related to the degraded signal, blur statistics, and constraint parameters. The solution which minimizes the energy function of the neural network is thus obtained iteratively by the simulated annealing algorithm. Simulation results show the effectiveness of the proposed algorithm which has, in addition, the capability of imposing level constraints on the original signal.

Citation Download Citation

Mehmet Bilgen and Hsien-Sen Hung "Application of neural network to restoration of signals degraded by a stochastic, shift-variant impulse response function and additive noise", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48384

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