Linear programming solutions to problems in logical inference and space-variant image restoration

Ramji V. Digumarthi; Paul Max Payton; Eamon B. Barrett

doi:10.1117/12.46478

1 August 1991 Linear programming solutions to problems in logical inference and space-variant image restoration

Ramji V. Digumarthi, Paul Max Payton, Eamon B. Barrett

Proceedings Volume 1472, Image Understanding and the Man-Machine Interface III; (1991) https://doi.org/10.1117/12.46478
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

Image understanding is a cross-disciplinary field, drawing on concepts and algorithms from image processing, pattern recognition, and artificial intelligence. An integrated system for image understanding may require a variety of capabilities that appear quite disparate, such as image restoration to compensate for degradations detected in the data, followed by logical inference to interpret features extracted from the restored data. The authors establish that constrained optimization provides a uniform formulation for two such apparently disparate problems: restoration of blurred imagery, and logical deduction or mechanized inference. Formulation of these problems in each of these categories as linear programming (LP) problems is shown. The 'deblurred' image is regained by minimizing a linear objective function subject to the constraints imposed by the blur. The degree of truth or falsity of a consequent proposition is established by maximizing a linear objective function subject to the constraints imposed by the premises.

Citation Download Citation

Ramji V. Digumarthi, Paul Max Payton, and Eamon B. Barrett "Linear programming solutions to problems in logical inference and space-variant image restoration", Proc. SPIE 1472, Image Understanding and the Man-Machine Interface III, (1 August 1991); https://doi.org/10.1117/12.46478

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