Embedded Processing for Extended Depth of Field Imaging Systems: From Infinite Impulse Response Wiener Filter to Learned Deconvolution

Autor: Alice Fontbonne, Pauline Trouvé-Peloux, Frédéric Champagnat, Gabriel Jobert, Guillaume Druart

Publikováno v: Sensors, Vol 23, Iss 23, p 9462 (2023)

Many works in the state of the art are interested in the increase of the camera depth of field (DoF) via the joint optimization of an optical component (typically a phase mask) and a digital processing step with an infinite deconvolution support or a

Externí odkaz: https://doaj.org/article/7078eaee42c74bdebb55fa7b871e8014

Learning local depth regression from defocus blur by soft-assignment encoding

Autor: Rémy Leroy, Pauline Trouvé-Peloux, Bertrand Le Saux, Benjamin Buat, Frédéric Champagnat

Publikováno v: Applied optics. 61(29)

We present a novel, to the best of our knowledge, patch-based approach for depth regression from defocus blur. Most state-of-the-art methods for depth from defocus (DFD) use a patch classification approach among a set of potential defocus blurs relat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::098f1dcc25b5698b771fce42eb5e199e
https://pubmed.ncbi.nlm.nih.gov/36256020

Learning scene and blur model for active chromatic depth from defocus

Autor: Frédéric Champagnat, Benjamin Buat, Guy Le Besnerais, Pauline Trouvé-Peloux

Publikováno v: Applied optics. 60(31)

In this paper, we propose what we believe is a new monocular depth estimation algorithm based on local estimation of defocus blur, an approach referred to as depth from defocus (DFD). Using a limited set of calibration images, we directly learn image

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7acaf1a7438f170fa2de19ec7c4b908
https://pubmed.ncbi.nlm.nih.gov/34807187

Performance model of depth from defocus with an unconventional camera

Autor: Guillaume Druart, G. Le Besnerais, Jérôme Idier, Pauline Trouvé-Peloux, Frédéric Champagnat

Publikováno v: Journal of the Optical Society of America. A Optics, Image Science, and Vision
Journal of the Optical Society of America. A Optics, Image Science, and Vision, Optical Society of America, 2021, 38 (10), pp.1489. ⟨10.1364/josaa.424621⟩
Journal of the Optical Society of America. A Optics, Image Science, and Vision, 2021, 38 (10), pp.1489. ⟨10.1364/josaa.424621⟩

International audience; In this paper we present a generic performance model able to evaluate the accuracy of depth estimation using depth from defocus. This model only requires the sensor PSF at a given depth to evaluate the theoretical accuracy of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8957732221eb51a4d7b47390fb17ab0f
https://hal.archives-ouvertes.fr/hal-03378595

Active chromatic depth from defocus for industrial inspection

Autor: Benjamin Buat, Thierry Simon, Pauline Trouvé-Peloux, Frédéric Champagnat, Guy Le Besnerais

Publikováno v: Unconventional Optical Imaging II.

In this paper we propose a new concept for a compact 3D sensor dedicated to industrial inspection, combining chromatic Depth From Defocus (DFD) and structured illumination. Depth is estimated from a single image using local estimation of the defocus

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::77531e35b4a7acaef1183a9ba72dcee2
https://doi.org/10.1117/12.2554514