dc.contributor.author |
De Villiers, Johan P
|
|
dc.date.accessioned |
2010-09-10T10:44:03Z |
|
dc.date.available |
2010-09-10T10:44:03Z |
|
dc.date.issued |
2010-06 |
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dc.identifier.citation |
De Villiers, JP. 2010. Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations. 7th International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa, Franschhoek, South Africa, 21-23 June 2010, pp 10 |
en |
dc.identifier.isbn |
978-1-4503-0118-3 |
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dc.identifier.uri |
http://hdl.handle.net/10204/4350
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dc.description |
7th International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa, Franschhoek, South Africa, 21-23 June 2010. |
en |
dc.description.abstract |
Improving the quality of an image increases the probability, speed and accuracy with which possible objects of interest can be located and identified. Image sharpening, in particular, can correct for soft focus and strengthen the outlines of objects thus improving the identification and segmentation both by automatic means and by man in the loop systems. Output pixel independence is ensured so that a GPU can be used to sharpen the pixels in parallel, achieving processing performance increases of 20-360 folds. This work provides a metric which can quantify the sharpness of an image and shows that the sharpness of live video can easily be doubled in real-time on commercial desktop computers without inducing excessive noise. |
en |
dc.language.iso |
en |
en |
dc.publisher |
Association for Computing Machinery |
en |
dc.subject |
Image sharpness |
en |
dc.subject |
Image sharpening |
en |
dc.subject |
GPU |
en |
dc.subject |
Real-time sharpening |
en |
dc.subject |
Computer graphics |
en |
dc.subject |
Virtual reality |
en |
dc.title |
Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations |
en |
dc.type |
Conference Presentation |
en |
dc.identifier.apacitation |
De Villiers, J. P. (2010). Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations. Association for Computing Machinery. http://hdl.handle.net/10204/4350 |
en_ZA |
dc.identifier.chicagocitation |
De Villiers, Johan P. "Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations." (2010): http://hdl.handle.net/10204/4350 |
en_ZA |
dc.identifier.vancouvercitation |
De Villiers JP, Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations; Association for Computing Machinery; 2010. http://hdl.handle.net/10204/4350 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - De Villiers, Johan P
AB - Improving the quality of an image increases the probability, speed and accuracy with which possible objects of interest can be located and identified. Image sharpening, in particular, can correct for soft focus and strengthen the outlines of objects thus improving the identification and segmentation both by automatic means and by man in the loop systems. Output pixel independence is ensured so that a GPU can be used to sharpen the pixels in parallel, achieving processing performance increases of 20-360 folds. This work provides a metric which can quantify the sharpness of an image and shows that the sharpness of live video can easily be doubled in real-time on commercial desktop computers without inducing excessive noise.
DA - 2010-06
DB - ResearchSpace
DP - CSIR
KW - Image sharpness
KW - Image sharpening
KW - GPU
KW - Real-time sharpening
KW - Computer graphics
KW - Virtual reality
LK - https://researchspace.csir.co.za
PY - 2010
SM - 978-1-4503-0118-3
T1 - Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations
TI - Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations
UR - http://hdl.handle.net/10204/4350
ER -
|
en_ZA |