Statistically Weighted Non-Local Method of Iterative Digital Image Processing

Hiram E. Hart

doi:10.1117/12.936649

9 January 1984 Statistically Weighted Non-Local Method of Iterative Digital Image Processing

Hiram E. Hart

Proceedings Volume 0432, Applications of Digital Image Processing VI; (1984) https://doi.org/10.1117/12.936649
Event: 27th Annual Technical Symposium, 1983, San Diego, United States

Abstract

A direct non-local iterative deconvolution method (NLM) employing the algorithm has been developed and successfully applied to tomographic radioisotopic tissue concentration imaging: PSRF are the point source response functions of the measurement system, (x,y,z) are the coordinates of the tissue element, and D(X,Y,Z) are the data elements corresponding to the measurement system indexing coordinates (X,Y,Z). High resolution determination of radioisotopic tissue concentrations on a scale aproximating the pixel spacing are routinely achieved even with relatively broad PSRF's and even though the individual data elements necessarily reflect a significant degree of radioisotopic statistical fluctuation. NLM converges to the correct high resolution source distributions with ideal and/or randomized data over a much wider range of conditions than the Gauss-Seidel method of iterative deconvolution. Comparative results will be presented.

Citation Download Citation

Hiram E. Hart "Statistically Weighted Non-Local Method of Iterative Digital Image Processing", Proc. SPIE 0432, Applications of Digital Image Processing VI, (9 January 1984); https://doi.org/10.1117/12.936649

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