Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm

How to cite: PA, P.; Arockiaraj, F.G.; Gopinath, S.; Smith, D.; Kahro, T.; Valdma, S.; Bleahu, A.; Reddy, A.N.K.; Katkus, T.; John Francis Rajeswary, A.S.; Ganeev, R.A.; Pikker, S.; Kukli, K.; Tamm, A.; Juodkazis, S.; Anand, V. Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm. Preprints 2022, 2022080010. https://doi.org/10.20944/preprints202208.0010.v1 PA, P.; Arockiaraj, F.G.; Gopinath, S.; Smith, D.; Kahro, T.; Valdma, S.; Bleahu, A.; Reddy, A.N.K.; Katkus, T.; John Francis Rajeswary, A.S.; Ganeev, R.A.; Pikker, S.; Kukli, K.; Tamm, A.; Juodkazis, S.; Anand, V. Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm. Preprints 2022, 2022080010. https://doi.org/10.20944/preprints202208.0010.v1

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MDPI and ACS Style

PA, P.; Arockiaraj, F.G.; Gopinath, S.; Smith, D.; Kahro, T.; Valdma, S.; Bleahu, A.; Reddy, A.N.K.; Katkus, T.; John Francis Rajeswary, A.S.; Ganeev, R.A.; Pikker, S.; Kukli, K.; Tamm, A.; Juodkazis, S.; Anand, V. Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm. Preprints 2022, 2022080010. https://doi.org/10.20944/preprints202208.0010.v1

APA Style

PA, P., Arockiaraj, F.G., Gopinath, S., Smith, D., Kahro, T., Valdma, S., Bleahu, A., Reddy, A.N.K., Katkus, T., John Francis Rajeswary, A.S., Ganeev, R.A., Pikker, S., Kukli, K., Tamm, A., Juodkazis, S., & Anand, V. (2022). Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm. Preprints. https://doi.org/10.20944/preprints202208.0010.v1

Chicago/Turabian Style

PA, P., Saulius Juodkazis and Vijayakumar Anand. 2022 "Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm" Preprints. https://doi.org/10.20944/preprints202208.0010.v1

Abstract

A refractive lens is one of the simplest, cost-effective and easily available imaging elements. With a spatially incoherent illumination, a refractive lens can faithfully map every object point to an image point in the sensor plane, when the object and image distances satisfy the imaging conditions. However, static imaging is limited to the depth of focus, beyond which the point-to-point mapping can be only obtained by changing either the location of the lens or the imaging sensor. In this study, the depth of focus of a refractive lens in static mode has been expanded using a recently developed computational reconstruction method, Lucy-Richardson-Rosen algorithm (LRRA). The technique consists of three steps. In this first step, the point spread functions (PSFs) were recorded along different depths and stored in the computer as PSF library. In the next step, the object intensity distribution was recorded. The LRRA was then applied to deconvolve the object information from the recorded intensity distributions in the final step. The results of LRRA were compared against two well-known reconstruction methods namely Lucy-Richardson algorithm and non-linear reconstruction.

Supplementary and Associated Material

https://zenodo.org/record/6928454: Theoretical simulation data

Keywords

imaging; incoherent optics; Lucy-Richardson-Rosen algorithm; deblurring; refractive lens; com-putational imaging; holography; 3D imaging; deconvolution

Subject

Physical Sciences, Optics and Photonics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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