Proceedings Paper
Image enhancement using hierarchical Bayesian image expansion super resolution| Format | Member Price | Non-Member Price |
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Paper Abstract
Multiframe super-resolution uses the information from a set of low resolution images to produce a high resolution output image. This process can prospectively be run several times with interim sets of enhanced images that can be further enhanced. This paper presents and discusses the results of this hierarchical technique on a sreated set of images and the results produced. When successful, this approach is able to produce a better quality image than the traditional single run super resolution approach. This provides a method for existing super resolution algorithms to further enhance image quality without modifying the underlying algorithm.
Paper Details
Date Published: 21 May 2015
PDF: 6 pages
Proc. SPIE 9497, Mobile Multimedia/Image Processing, Security, and Applications 2015, 949709 (21 May 2015); doi: 10.1117/12.2178179
Published in SPIE Proceedings Vol. 9497:
Mobile Multimedia/Image Processing, Security, and Applications 2015
Sos S. Agaian; Sabah A. Jassim; Eliza Yingzi Du, Editor(s)
PDF: 6 pages
Proc. SPIE 9497, Mobile Multimedia/Image Processing, Security, and Applications 2015, 949709 (21 May 2015); doi: 10.1117/12.2178179
Show Author Affiliations
Timothy Whitney, Univ. of North Dakota (United States)
Jeremy Straub, Univ. of North Dakota (United States)
Jeremy Straub, Univ. of North Dakota (United States)
Ronald Marsh, Univ. of North Dakota (United States)
Published in SPIE Proceedings Vol. 9497:
Mobile Multimedia/Image Processing, Security, and Applications 2015
Sos S. Agaian; Sabah A. Jassim; Eliza Yingzi Du, Editor(s)
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