EURASIP Journal on Advances in Signal Processing
Volume 2008 (2008), Article ID 281486, 17 pages
doi:10.1155/2008/281486
Research Article

Detection and Correction of Under-/Overexposed Optical Soundtracks by Coupling Image and Audio Signal Processing

1Laboratoire Informatique, Image, Interaction, Université de La Rochelle, 17042 La Rochelle, France
2Centre de Morphologie Mathématique, Ecole Nationale Supérieure des Mines de Paris, 77305 Fontainebleau, France

Received 2 October 2007; Revised 15 June 2008; Accepted 26 June 2008

Academic Editor: Anil Kokaram

Copyright © 2008 Jonathan Taquet et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Film restoration using image processing, has been an active research field during the last years. However, the restoration of the soundtrack has been mainly performed in the sound domain, using signal processing methods, despite the fact that it is recorded as a continuous image between the images of the film and the perforations. While the very few published approaches focus on removing dust particles or concealing larger corrupted areas, no published works are devoted to the restoration of soundtracks degraded by substantial underexposure or overexposure. Digital restoration of optical soundtracks is an unexploited application field and, besides, scientifically rich, because it allows mixing both image and signal processing approaches. After introducing the principles of optical soundtrack recording and playback, this contribution focuses on our first approaches to detect and cancel the effects of under and overexposure. We intentionally choose to get a quantification of the effect of bad exposure in the 1D audio signal domain instead of 2D image domain. Our measurement is sent as feedback value to an image processing stage where the correction takes place, building up a “digital image and audio signal” closed loop processing. The approach is validated on both simulated alterations and real data.