Performance Comparison of Optimization Methods for Blind Deconvolution

Daniel Thompson, Boeing, Brandoch Calef, Boeing, Michael Werth, Boeing

Keywords: Optimization, MFBD, Imaging

Abstract:

There are many methods that will solve high dimensional regression problems, and choosing an appropriate method can be challenging. For some problems, accuracy holds precedence over speed whereas in other instances speed is required for a large number of problem sets. In this paper we study the performance of several methods that solve the multiframe blind deconvolution problem by comparing speed and accuracy of each algorithm, highlighting the merits of each algorithm.

Date of Conference: September 20-23, 2016

Track: Poster

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