Fast thresholded multi-channel Landweber algorithm for wavelet-regularized multi-angle deconvolution

Nikhil Chacko; Michael Liebling

doi:10.1117/12.2024648

26 September 2013 Fast thresholded multi-channel Landweber algorithm for wavelet-regularized multi-angle deconvolution

Nikhil Chacko, Michael Liebling

Proceedings Volume 8858, Wavelets and Sparsity XV; 885819 (2013) https://doi.org/10.1117/12.2024648
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

Abstract

3D deconvolution in optical wide eld microscopy aims at recovering optical sections through thick objects. Acquiring data from multiple, mutually-tilted directions helps ll the missing cone of information in the optical transfer function, which normally renders the deconvolution problem particularly ill-posed. Here, we propose a fast-converging iterative deconvolution method for multi-angle deconvolution microscopy. Specically, we formulate the imaging problem using a lter-bank structure, and present a multi-channel variation of a thresholded Landweber deconvolution algorithm with wavelet-sparsity regularization. Decomposition of the minimization problem into subband-dependent terms ensures fast convergence. We demonstrate the applicability of the algorithm via simulation results.

Citation Download Citation

Nikhil Chacko and Michael Liebling "Fast thresholded multi-channel Landweber algorithm for wavelet-regularized multi-angle deconvolution", Proc. SPIE 8858, Wavelets and Sparsity XV, 885819 (26 September 2013); https://doi.org/10.1117/12.2024648

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