Minimal data collection: imaging from limited-angle data using prior knowledge

Michael A. Fiddy; Robert V. McGahan; Drew A. Pommet

doi:10.1117/12.284712

9 December 1997 Minimal data collection: imaging from limited-angle data using prior knowledge

Michael A. Fiddy, Robert V. McGahan, Drew A. Pommet

Proceedings Volume 3171, Computational, Experimental, and Numerical Methods for Solving Ill-Posed Inverse Imaging Problems: Medical and Nonmedical Applications; (1997) https://doi.org/10.1117/12.284712
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

We describe a method for generating a high resolution image or target identifier from limited sampled noisy Fourier data. These data are assumed to be collected from either limited-angle tomographic data or limited-angle scattering data. In extreme cases of, for example, only backscatter data being measured, little useful image information can be deduced directly from the available measurements. However, if some a prior knowledge about the support and/or internal features of the object can be assumed, this information can be incorporated into a spectral estimation technique we refer to as the PDFT. This technique has a closed form solution that estimates the image and is easily regularized in the Miller-Tikhonov sense. We have studied how the availability of less and less data affects the resulting image quality when using the PDFT. We explain the trade-offs between reducing the number of measurements (e.g. for time or radiation exposure considerations) and the resulting image fidelity. We also discuss how little data need be measured to be able to identify a given object when good a priori information is available. Examples using real data are presented.

Citation Download Citation

Michael A. Fiddy, Robert V. McGahan, and Drew A. Pommet "Minimal data collection: imaging from limited-angle data using prior knowledge", Proc. SPIE 3171, Computational, Experimental, and Numerical Methods for Solving Ill-Posed Inverse Imaging Problems: Medical and Nonmedical Applications, (9 December 1997); https://doi.org/10.1117/12.284712

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