Perceptual Image Fusion Using Wavelets
- Submitting institution
-
University of Bristol
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 203979215
- Type
- D - Journal article
- DOI
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10.1109/TIP.2016.2633863
- Title of journal
- IEEE Transactions on Image Processing
- Article number
- 7762914
- First page
- 1076
- Volume
- 26
- Issue
- 3
- ISSN
- 1057-7149
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2016
- 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
-
2
- Research group(s)
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C - Visual Information Lab
- Citation count
- 26
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The first perceptual image fusion method based on a rigorous approach using explicit luminance and contrast masking models, giving improved quantitative and qualitative results. Originated from collaborations with General Dynamics and DSTL under the UK MoD Defence Technology Centre in Data and Information Fusion (https://web.archive.org/web/20060626043544/http://www.difdtc.com/). Underpinning work related to this contribution informed the development of the RFEL Trailblazer Vision system (https://www.rfel.com/product/trailblazer/), and advances in our CLEAR2 algorithm for mitigating atmospheric distortions, assessed by US DoD (Vaytek) as best in class. It formed a key pillar in our EPSRC Platform Grant, Vision for the Future (2015-20, PI:Bull/EP/M000885/1).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -