Convolutional neuronal network to restore images encoded by a wavefront coding imaging system

José M. Reyes-Alfaro; Carina Toxqui-Quitl; María A. Espejel Rivera; Enrique González Amador; Alfonso Padilla-Vivanco

doi:10.1117/12.2677797

2 October 2023 Convolutional neuronal network to restore images encoded by a wavefront coding imaging system

José M. Reyes-Alfaro, Carina Toxqui-Quitl, María A. Espejel Rivera, Enrique González Amador, Alfonso Padilla-Vivanco

Proceedings Volume 12666, Current Developments in Lens Design and Optical Engineering XXIV; 126660J (2023) https://doi.org/10.1117/12.2677797
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Conference Poster

Abstract

Wavefront coding (WFC) technique has been used to extend the depth of field (DoF) in an imaging system. Its effectiveness lies in using a phase mask (PM), which allows the point spread function (PSF) to remain almost invariant in an axial range of the DoF. Subsequently, a restoration method of the acquired coded images is required. An optical-computational technique that uses Trefoil profile PM for encoding and a convolutional neural network (CNN) to restore is presented. Comparative results are done between the restored image using the Wiener filter and the one obtained with a CNN. An image quality evaluation is done in terms of spatial resolution and contrast.

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

Citation Download Citation

José M. Reyes-Alfaro, Carina Toxqui-Quitl, María A. Espejel Rivera, Enrique González Amador, and Alfonso Padilla-Vivanco "Convolutional neuronal network to restore images encoded by a wavefront coding imaging system", Proc. SPIE 12666, Current Developments in Lens Design and Optical Engineering XXIV, 126660J (2 October 2023); https://doi.org/10.1117/12.2677797

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