Superresolution Using Incoherent Light and the Least Squares Method
Abstract
This thesis discusses the problem of incoherent imaging in a diffraction-limited optical system. Its purpose was to prove that resolving two incoherent point sources of light is possible and achievable under certain circumstances. The effects of noise are considered when trying to super-resolve the two incoherent objects. The analysis assumes a finite object of known maximum extent with an estimation of the noise in the system. The noise is assumed to be Gaussian, white, and additive for all spatial frequencies. The superresolution process uses the standard least squares process to achieve minimum error with a smoothing or regularization procedure. The singular values of the transfer matrix are modified to attenuate the very small singular values to avoid noise amplification in the high order terms. The effect of the noise is overcome by the use of a smoothing parameter. The superresolution process works extremely well when the extent of the object is known a priori to have a certain bound or maximum. Components of the restored or processed object outside the known bounds are attenuated. Results indicate that band-pass pupils can super- resolve with only limited knowledge of the object when the smoothing parameter is used. Keywords: Optical filters; Image restoration.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1985
- Accession Number
- ADA163964
Entities
People
- Robert F. Stierwalt
Organizations
- Air Force Institute of Technology