A fast, simple, and parallelizable deconvolution algorithm for real-time applications

Daniel Williams

doi:10.1117/12.2677259

4 October 2023 A fast, simple, and parallelizable deconvolution algorithm for real-time applications

Daniel Williams

Proceedings Volume 12674, Applications of Digital Image Processing XLVI; 126740B (2023) https://doi.org/10.1117/12.2677259
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

We present a fast, simple, and parallelizable deconvolution algorithm for the real-time deblurring of one- or two- dimensional signals (i.e. images) degraded by defocus or bokeh-like blur. The proposed algorithm runs in linear- time and performs significantly faster than other popular deconvolution methods tested, bringing the deblurring time down to under 10ms for full-HD images. It has a simple software implementation, requiring no Fourier transforms or dynamic memory allocation. Its parallel design makes it especially suitable for GPU acceleration. For one-dimensional noise-free signals, the algorithm is proven to converge exactly to the original un-blurred signal.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Daniel Williams "A fast, simple, and parallelizable deconvolution algorithm for real-time applications", Proc. SPIE 12674, Applications of Digital Image Processing XLVI, 126740B (4 October 2023); https://doi.org/10.1117/12.2677259

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