Image fusion and enhancement using triangulated irregular networks

Scarmana, G. (2017) Image fusion and enhancement using triangulated irregular networks. In: Videometrics, Range Imaging and Applications XIV Conference , 26-29 June 2017, Munich, Germany.

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.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright © 2017, Society of Photo-Optical Instrumentation Engineers.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 06 Sep 2017 01:47
Last Modified: 21 Jun 2018 01:09
Uncontrolled Keywords: image enhancement; triangulated irregular network; image fusion; networks; image composite; video
Fields of Research : 01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences
Identification Number or DOI: 10.1117/12.2279443
URI: http://eprints.usq.edu.au/id/eprint/32769

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