Information, language, and pixon-based image reconstruction

Richard Charles Puetter

doi:10.1117/12.255082

25 October 1996 Information, language, and pixon-based image reconstruction

Richard Charles Puetter

Proceedings Volume 2827, Digital Image Recovery and Synthesis III; (1996) https://doi.org/10.1117/12.255082
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

From an information theoretic point of view, the inverse problem and the problem of data compression are intimately related. Optimal compression seeks the most concise representation of a data set, while Bayesian probability theory favors image reconstruction algorithms which minimally model the information present in the data. This should not be surprising. It is in keeping with a scientist's intuitive need to satisfy the precepts of Occam's Razor, i.e. not to over interpret one's data. Information scientists might describe this process as quantifying the algorithmic information content (AIC) of the image, and then using this 'coordinate system' for optimal image reconstruction. The present paper describes pixon- based image reconstruction, a technique based upon AIC minimal image models. Because AIC is language dependent (description length and language complexity are inversely related) we have based the practical implementation of our method on concise (descriptive) languages for generic images, e.g. multiresolution basis functions. The present paper describes both the theory of pixon-based reconstruction and presents practical examples demonstrating that pixon-based reconstruction produces results consistently superior (often by large factors) to those of other methods, including the best examples of maximum likelihood and maximum entropy image reconstruction.

Citation Download Citation

Richard Charles Puetter "Information, language, and pixon-based image reconstruction", Proc. SPIE 2827, Digital Image Recovery and Synthesis III, (25 October 1996); https://doi.org/10.1117/12.255082

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