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.

Fanfani M., Colombo C., Bellavia F. (2021). Restoration and Enhancement of Historical Stereo Photos Through Optical Flow. In A. Del Bimbo, R. Cucchiara, R. Vezzani (a cura di), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 643-656). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-68796-0_46].

Restoration and Enhancement of Historical Stereo Photos Through Optical Flow

Bellavia F.
2021-01-01

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
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
Fanfani M., Colombo C., Bellavia F. (2021). Restoration and Enhancement of Historical Stereo Photos Through Optical Flow. In A. Del Bimbo, R. Cucchiara, R. Vezzani (a cura di), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 643-656). Springer Science and Business Media Deutschland GmbH [10.1007/978-3-030-68796-0_46].
File in questo prodotto:
File Dimensione Formato  
FAPER2020.pdf

Solo gestori archvio

Tipologia: Versione Editoriale
Dimensione 1.92 MB
Formato Adobe PDF
1.92 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
paper_lncs.pdf

accesso aperto

Tipologia: Post-print
Dimensione 2.47 MB
Formato Adobe PDF
2.47 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/509283
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact