Iterative Reconstruction Of Space-Limited Images

C. K. Rushforth; R. L. Frost

doi:10.1117/12.958838

22 August 1980 Iterative Reconstruction Of Space-Limited Images

C. K. Rushforth, R. L. Frost

Proceedings Volume 0231, 1980 Intl Optical Computing Conf I; (1980) https://doi.org/10.1117/12.958838
Event: 1980 Technical Symposium East, 1980, Washington, D.C., United States

Abstract

This paper describes an approach to the problem of reconstructing a star which has been blurred by atmospheric turbulence and further corrupted by sensor noise. The Knox-Thompson speckle-imaging technique is used to obtain initial estimates of the amplitude and phase spectra of the object. When the noise level is high, these estimates are quite inaccurate at the higher spatial frequencies, and the associated reconstruction is very poor. We attempted to alleviate the problem by throwing away the noisy high-frequency terms and then using a spectral extrapolation algorithm to reconstruct them from the more accurate low frequencies. Spectral extrapolation was done using both the Gerchberg algorithm and a new algorithm described in the paper. These two algorithms and others are discussed in terms of a convenient eigenfunction expansion, and some experimental results are presented. Although these particular results favor the new algorithm, general conclusions must be drawn with caution.

Citation Download Citation

C. K. Rushforth and R. L. Frost "Iterative Reconstruction Of Space-Limited Images", Proc. SPIE 0231, 1980 Intl Optical Computing Conf I, (22 August 1980); https://doi.org/10.1117/12.958838

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