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Compressive Dual Photography.

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Bibliographic Details
Title: Compressive Dual Photography.
Authors: Sen, Pradeep1, Darabi, Soheil1
Source: Computer Graphics Forum. Apr2009, Vol. 28 Issue 2, p609-618. 10p. 3 Color Photographs, 4 Black and White Photographs, 1 Chart.
Subjects: Digital image processing software, Digitization, Computer graphics research, Computer graphics software, Digital photography software, Algorithms
Abstract: The accurate measurement of the light transport characteristics of a complex scene is an important goal in computer graphics and has applications in relighting and dual photography. However, since the light transport data sets are typically very large, much of the previous research has focused on adaptive algorithms that capture them efficiently. In this work, we propose a novel, non-adaptive algorithm that takes advantage of the compressibility of the light transport signal in a transform domain to capture it with less acquisitions than with standard approaches. To do this, we leverage recent work in the area of compressed sensing, where a signal is reconstructed from a few samples assuming that it is sparse in a transform domain. We demonstrate our approach by performing dual photography and relighting by using a much smaller number of acquisitions than would normally be needed. Because our algorithm is not adaptive, it is also simpler to implement than many of the current approaches. [ABSTRACT FROM AUTHOR]
Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Computer+Graphics+Forum%22">Computer Graphics Forum</searchLink>. Apr2009, Vol. 28 Issue 2, p609-618. 10p. 3 Color Photographs, 4 Black and White Photographs, 1 Chart.
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  Data: <searchLink fieldCode="DE" term="%22Digital+image+processing+software%22">Digital image processing software</searchLink><br /><searchLink fieldCode="DE" term="%22Digitization%22">Digitization</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics+research%22">Computer graphics research</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics+software%22">Computer graphics software</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+photography+software%22">Digital photography software</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
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  Data: The accurate measurement of the light transport characteristics of a complex scene is an important goal in computer graphics and has applications in relighting and dual photography. However, since the light transport data sets are typically very large, much of the previous research has focused on adaptive algorithms that capture them efficiently. In this work, we propose a novel, non-adaptive algorithm that takes advantage of the compressibility of the light transport signal in a transform domain to capture it with less acquisitions than with standard approaches. To do this, we leverage recent work in the area of compressed sensing, where a signal is reconstructed from a few samples assuming that it is sparse in a transform domain. We demonstrate our approach by performing dual photography and relighting by using a much smaller number of acquisitions than would normally be needed. Because our algorithm is not adaptive, it is also simpler to implement than many of the current approaches. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/j.1467-8659.2009.01401.x
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      – Code: eng
        Text: English
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        PageCount: 10
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      – SubjectFull: Digital image processing software
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      – SubjectFull: Digitization
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      – SubjectFull: Computer graphics research
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      – SubjectFull: Computer graphics software
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      – SubjectFull: Digital photography software
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              Text: Apr2009
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