Scene-and-Process-Dependent Spatial Image Quality Metrics
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- qx443
- Type
- D - Journal article
- DOI
-
10.2352/J.ImagingSci.Technol.2019.63.6.060407
- Title of journal
- Journal of Imaging Science and Technology
- Article number
- -
- First page
- 060407-1
- Volume
- 63
- Issue
- 6
- ISSN
- 1943-3522
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Measures of camera performance, introduced in a recent publication from the same authors, are incorporated in existing and two novel visual image quality metrics. The significance of the work lies in the transformation of standardised (IEEE, ISO) traditional image quality metrics that previously failed to predict the visual quality of non-linear in-camera processes and also in the introduction of two simple and elegant signal-to-noise models for predicting digital camera quality. The success of the proposed metrics/metric transformations is evident from their rigorous validation against the most popular metrics used by the imaging industries. Journal reviewer: “Very interesting and novel work."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
