Massively parallel image restoration

Murali M. Menon

doi:10.1117/12.44877

1 August 1991 Massively parallel image restoration

Murali M. Menon

Proceedings Volume 1471, Automatic Object Recognition; (1991) https://doi.org/10.1117/12.44877
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

An image restoration method that performs piecewise smooth restorations on images corrupted with very high noise levels is presented. The restoration is based on a Markov random field (MRF) model using a neural network sigmoid nonlinearity between pixels to produce a restoration with sharp boundaries while providing noise reduction. The model is currently implemented using an efficient deterministic search algorithm that typically requires less than 200 iterations in a digital computer simulation. The algorithm is able to restore images with up to 71% of the pixels corrupted with sensor noise (non-gaussian). Results from simulation indicate that the MRF restoration is capable of operating at signal-to-noise ratios 5 to 6 dB lower than the median filtering. The same model can be applied to a large number of sensor measurements (Doppler, intensity, passive infrared, range, and video sensors) by simply adjusting a single parameter. This is especially relevant for hardware implementation, since a single chip can be used for processing a wide variety of imagery. The model has a massively parallel architecture with local neighbor interactions (four nearest neighbors), and can be implemented on a large parallel computer or a custom analog VLSI chip. Implementation of the model in analog VLSI would allow video rate restoration of 512 X 512 pixel images.

Citation Download Citation

Murali M. Menon "Massively parallel image restoration", Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); https://doi.org/10.1117/12.44877

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