Image fusion and enhancement using triangulated irregular networks

Paper


Scarmana, G.. 2017. "Image fusion and enhancement using triangulated irregular networks." Remondino, Fabio and Shortis, Mark R. (ed.) Videometrics, Range Imaging and Applications XIV Conference . Munich, Germany 26 - 29 Jun 2017 Bellingham, Washington, United States. https://doi.org/10.1117/12.2279443
Paper/Presentation Title

Image fusion and enhancement using triangulated irregular networks

Presentation TypePaper
Authors
AuthorScarmana, G.
EditorsRemondino, Fabio and Shortis, Mark R.
Journal or Proceedings TitleProceedings of SPIE: Videometrics, Range Imaging, and Applications XIV
Journal Citation10332
Number of Pages7
Year2017
Place of PublicationBellingham, Washington, United States
ISBN9781510611092
9781510611108
Digital Object Identifier (DOI)https://doi.org/10.1117/12.2279443
Conference/Event Videometrics, Range Imaging and Applications XIV Conference
Conference on Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection
Event Details
Videometrics, Range Imaging and Applications XIV Conference
Event Date
26 to end of 29 Jun 2017
Event Location
Munich, Germany
Event Details
Conference on Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection
Abstract

A triangulated irregular network (TIN) is a viable structure for vector representation of raster image data. To visualize the image characterized by triangulation, it is required to fit a continuous surface of pixel brightness values in the triangulation (i.e. to interpolate data stored in its vertices). From this perspective, this paper presents a multi-frame image fusion and enhancement process that employs TIN structures rather than arrays of pixels as the original working units. The feasibility of this application relates to the fact that a TIN model offers a good quality digital image representation with a reduced density of pixel values as compared to a corresponding raster representation [4]. In the proposed process several low-resolution unregistered and compressed images (such as those extracted from a video footage) of a common scene are: (a) registered to a sub-pixel level (b) transformed to a TIN structure, (c) grouped or mapped globally within a singular framework to create a denser TIN composite, and (d) the TIN representation is used in reverse to reconstruct a higher resolution image in raster format with more details than any of the original input frames. Tests and subsequent results are shown to demonstrate the validity and accuracy of the proposed multi-frame image enhancement process. A comparison of this process of multi-frame image enhancement using various interpolation methods and practices is included. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Keywordsimage enhancement; triangulated irregular network; image fusion; networks; image composite; video
ANZSRC Field of Research 2020490501. Applied statistics
400607. Signal processing
469999. Other information and computing sciences not elsewhere classified
401304. Photogrammetry and remote sensing
460306. Image processing
Public Notes

File reproduced in accordance with the copyright policy of the publisher/author.

Byline AffiliationsSchool of Civil Engineering and Surveying
Institution of OriginUniversity of Southern Queensland
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