Redundancy reduction as the basis for visual signal processing

A. Norman Redlich

doi:10.1117/12.140085

1 July 1992 Redundancy reduction as the basis for visual signal processing

A. Norman Redlich

Proceedings Volume 1710, Science of Artificial Neural Networks; (1992) https://doi.org/10.1117/12.140085
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

An environmentally driven, self-organizing principle for encoding sensory messages is proposed, based on the need to learn their statistical properties. Optimal encodings are found for two cases: First, for linear maps the optimal transformation eliminates pairwise correlations between input `pixels.' This solution is applied to predict the retinal transform based on the autocorrelator for natural scenes. Second, when the input `images' consist of a set of weakly coupled, local `bound states,' then a series of non-linear maps is found which optimally segments the input. This is demonstrated by using it to efficiently learn, without supervision, the statistics of English text.

Citation Download Citation

A. Norman Redlich "Redundancy reduction as the basis for visual signal processing", Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); https://doi.org/10.1117/12.140085

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