In this paper, a new technique to reduce the noise in a reconstructed hologram image is proposed. Unlike all the techniques in the literature, the proposed approach not only takes into account spatial information but also temporal statistics associated with the pixels. This innovative solution enables, at first, the automatic detection of the areas of the image containing the objects (foreground). This way, all the pixels not belonging to any objects are directly cleaned up and the contrast between objects and background is consistently increased. The remaining pixels are then processed with a spatio-temporal filtering which cancels out the effects of speckle noise, while preserving the structural details of the objects. The proposed approach has been compared with other common speckle denoising techniques and it is found to give better both visual and quantitative results.

Automatic Digital Hologram Denoising by Spatiotemporal Analysis of Pixel-Wise Statistics

MEMMOLO, PASQUALE;DISTANTE, COSIMO;FERRARO, PIETRO;LEO, MARCO;PATURZO, MELANIA;MEUCCI, RICCARDO
2013

Abstract

In this paper, a new technique to reduce the noise in a reconstructed hologram image is proposed. Unlike all the techniques in the literature, the proposed approach not only takes into account spatial information but also temporal statistics associated with the pixels. This innovative solution enables, at first, the automatic detection of the areas of the image containing the objects (foreground). This way, all the pixels not belonging to any objects are directly cleaned up and the contrast between objects and background is consistently increased. The remaining pixels are then processed with a spatio-temporal filtering which cancels out the effects of speckle noise, while preserving the structural details of the objects. The proposed approach has been compared with other common speckle denoising techniques and it is found to give better both visual and quantitative results.
2013
Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" - ISASI
Istituto Nazionale di Ottica - INO
Istituto Nazionale di Ottica - INO
Istituto Nazionale di Ottica - INO
Holography
image denoising
statistical learning
adaptive filters
image segmentation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/263287
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