Paper
17 January 2006 Further image quality assessment in digital film restoration
Author Affiliations +
Proceedings Volume 6059, Image Quality and System Performance III; 60590S (2006) https://doi.org/10.1117/12.642414
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
Several digital film restoration techniques have emerged during the last decade and became more and more automated but restoration evaluation still remains a rarely tackled issue. In the sphere of cinema, the image quality is judged visually. In fact, experts and technicians judge and determine the quality of the film images during the calibration (post production) process. As a consequence, the quality of a movie is also estimated subjectively by experts in the field of digital film restoration. On the other hand, objective quality metrics do not necessarily correlate well with perceived quality. Plus, some measures assume that there exists a reference in the form of an "original" to compare to, which prevents their usage in digital restoration field, where often there is no reference to compare to. That is why subjective evaluation is the most used and most efficient approach up to now. But subjective assessment is expensive, time consuming and does not respond, hence, to the economic requirements. After presenting the several defects than can affect cinematographic material, and the film digital restoration field, we present in this paper the issues of image quality evaluation in the field of digital film restoration and suggest some reference free objective measures.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Chambah, C. Saint-Jean, F. Helt, and A. Rizzi "Further image quality assessment in digital film restoration", Proc. SPIE 6059, Image Quality and System Performance III, 60590S (17 January 2006); https://doi.org/10.1117/12.642414
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Image quality

Video

Image processing

Cameras

Visualization

Digital imaging

Quality measurement

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