High resolution imaging using phase retrieval, volume 2

Details High resolution imaging using phase retrieval, volume 2 High resolution imaging using phase retrieval, volume 2

Oct 1991

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1991eri..rept.....f&link_type=abstract

Final Report, Aug. 1986 - Dec. 1989 Environmental Research Inst. of Michigan, Ann Arbor. Advanced Concepts Div.

Statistics

Computation

Antimissile Defense, Distortion, Fourier Analysis, High Resolution, Images, Imaging Techniques, Interpolation, Telescopes, Algorithms, Amplitudes, Atmospheric Circulation, Computation, Evaluation, Frequencies, Interferometers, Interferometry, Performance Tests, Requirements, Spatial Distribution, Weight (Mass)

Scientific paper

This report describes a technique for obtaining fine-resolution images, suitable for SDI midcourse discrimination, using an inexpensive, lightweight telescope that would ordinarily yield a poor image. If, instead of collecting a blurred image with the telescope, one sends the light through an amplitude interferometer, then the modulus, but not the phase, of the Fourier transform of the object can be measured, despite the aberrations. We have developed and analyzed phase retrieval algorithms that recover the unknown Fourier phase, which allows a fine-resolution image to be reconstructed despite the aberrations of the telescope. It will also correct aberrations due to atmospheric turbulence for a ground-based telescope, and can be used with several other imaging modalities. For the case of interferometry through a partially obscured aperture, an algorithm was developed that combines phase retrieval with interpolation in order to restore the information at the missing spatial frequencies while retrieving the phase at the unobscured spatial frequencies. Another new phase retrieval algorithm, based on the Ayers/Dainty blind deconvolution algorithm, was also developed. A new methodology for exploring the uniqueness of phase retrieval in a practical sense was developed and tested. It involves finding the ambiguous image which is closest to a given image by a reduced-gradient search technique. The computational requirements for the phase retrieval algorithm were quantified. Laboratory experiments to test the technique were initiated.

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