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Application-specific tone mapping via genetic programming
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Debattista, Kurt (2018) Application-specific tone mapping via genetic programming. Computer Graphics Forum, 37 (1). pp. 439-450. doi:10.1111/cgf.13307
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Official URL: http://dx.doi.org/10.1111/cgf.13307
Abstract
High dynamic range (HDR) imagery permits the manipulation of real-world data distinct from the limitations of the traditional, low dynamic range (LDR), content. The process of retargetting HDR content to traditional LDR imagery via tone mapping operators (TMOs) is useful for visualising HDR content on traditional displays, supporting
backwards-compatible HDR compression and, more recently, is being frequently used for input into a wide variety of computer vision applications. This work presents the automatic generation of TMOs for specific applications via the evolutionary computing method of genetic programming (GP). A straightforward, generic GP method that generates TMOs for a given fitness function and HDR content is presented. Its efficacy is demonstrated in the context of three applications: visualisation of HDR content on LDR displays, feature mapping and compression. For these applications, results show good performance for the generated TMOs when compared to traditional methods. Furthermore, they demonstrate that the method is generalisable and could be used across various applications that require TMOs but for which dedicated successful TMOs have not yet been discovered.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
| Library of Congress Subject Headings (LCSH): | Image processing, Computer vision , Pattern recognition systems, Genetic programming (Computer science) | ||||||||
| Journal or Publication Title: | Computer Graphics Forum | ||||||||
| Publisher: | Blackwell Publishing | ||||||||
| ISSN: | 0167-7055 | ||||||||
| Official Date: | February 2018 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 6 November 2017 | ||||||||
| Volume: | 37 | ||||||||
| Number: | 1 | ||||||||
| Page Range: | pp. 439-450 | ||||||||
| DOI: | 10.1111/cgf.13307 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access | ||||||||
| RIOXX Funder/Project Grant: |
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