Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed. The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically and photometrically. Restoration is then accomplished by data fusion according to the stacked median, followed by gradient adjustment and iterative visual consistency checking. The obtained output is fully consistent with the original content, thus improving over the methods based on image hallucination. Comparative results on three different datasets of historical stereograms show the effectiveness of the proposed approach, and its superiority over single-image denoising and super-resolution methods. © 2021, Springer Nature Switzerland AG.

Restoration and Enhancement of Historical Stereo Photos Through Optical Flow / Fanfani, Marco; Colombo, Carlo; Bellavia, Fabio. - STAMPA. - 12663 LNCS:(2021), pp. 643-656. (Intervento presentato al convegno ICPR2020 International Workshop on Fine Art Pattern Extraction and Recognition FAPER2020) [10.1007/978-3-030-68796-0_46].

Restoration and Enhancement of Historical Stereo Photos Through Optical Flow

Fanfani, Marco;Colombo, Carlo;Bellavia, Fabio
2021

Abstract

Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed. The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically and photometrically. Restoration is then accomplished by data fusion according to the stacked median, followed by gradient adjustment and iterative visual consistency checking. The obtained output is fully consistent with the original content, thus improving over the methods based on image hallucination. Comparative results on three different datasets of historical stereograms show the effectiveness of the proposed approach, and its superiority over single-image denoising and super-resolution methods. © 2021, Springer Nature Switzerland AG.
2021
25th International Conference on Pattern Recognition Workshops, ICPR 2020
ICPR2020 International Workshop on Fine Art Pattern Extraction and Recognition FAPER2020
Fanfani, Marco; Colombo, Carlo; Bellavia, Fabio
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1355514
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