Title: BRDF Reconstruction Using Compressive Sensing
Authors: Seylan, Nurcan
Ergun, Serkan
Öztürk, Aydın
Citation: WSCG 2013: Full Papers Proceedings: 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in cooperation with EUROGRAPHICS Association, p. 88-94.
Issue Date: 2013
Publisher: Václav Skala - UNION Agency
Document type: konferenční příspěvek
URI: http://wscg.zcu.cz/WSCG2013/!_2013-WSCG-Full-proceedings.pdf
ISBN: 978-80-86943-74-9
Keywords: rekonstrukce obrazu;tlakové snímání
Keywords in different language: image reconstruction;compressive sensing
Abstract: Compressive sensing is a technique for efficiently acquiring and reconstructing the data. This technique takes advantage of sparseness or compressibility of the data, allowing the entire measured data to be recovered from relatively few measurements. Considering the fact that the BRDF data often can be highly sparse, we propose to employ the compressive sensing technique for an efficient reconstruction. We demonstrate how to use compressive sensing technique to facilitate a fast procedure for reconstruction of large BRDF data. We have showed that the proposed technique can also be used for the data sets having some missing measurements. Using BRDF measurements of various isotropic materials, we obtained high quality images at very low sampling rates both for diffuse and glossy materials. Similar results also have been obtained for the specular materials at slightly higher sampling rates.
Rights: © Václav Skala - UNION Agency
Appears in Collections:WSCG 2013: Full Papers Proceedings

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/10598

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