Super-resolution for 2.5D height data of microstructured surfaces using the vdsr network
Keyword(s):
In this work super-resolution imaging is used to enhance 2.5D height data of thermal sprayed Al2O3 ceramics with stochastically microstructured surfaces. The data is obtained by means of a confocal laser scanning microscope. By implementing and training a Very Deep Super-Resolution neural network to generate residual images an improvement of the peak signal-to-noise ratio and structural similarity index can be observed when compared to classic interpolation methods.
2008 ◽
Vol 130
(5)
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pp. 909-916
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1988 ◽
Vol 46
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pp. 96-97
1994 ◽
Vol 52
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pp. 164-165
1989 ◽
Vol 47
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pp. 134-135
Keyword(s):
2006 ◽
Vol 20
(4)
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pp. 435-439
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2019 ◽
Vol 10
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pp. 2182-2191
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