An application of the least squares plane fitting interpolation process to image reconstruction and enhancement

Scarmana, Gabriel (2016) An application of the least squares plane fitting interpolation process to image reconstruction and enhancement. In: 78th FIG Working Week 2016: Recovering from Disaster, 2-6 May 2016, Christchurch, New Zealand.

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This work applies a least squares plane fitting (LSP) method as an alternative way of interpolating irregularly spaced pixel intensity values that are suitable for image reconstruction of a static scene via super-resolution (SR). SR is a term used within the computer vision and image processing community to describe the process of reconstructing a high resolution image from a sequence of several shifted images covering the same scene.
The accuracy attainable by this process is estimated via tests where the simulation parameters are controlled and where the reconstructed high resolution image can be compared with its original. In these tests the original image is scanned randomly so as to create a sequence of low-resolution and JPEG compressed shifted images. The comparison is based on the r.m.s.e. of the differences between the reconstructed image and the original.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Proceedings:
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 26 Sep 2016 00:40
Last Modified: 10 Jul 2017 03:10
Uncontrolled Keywords: image enhancement, interpolation, least squares, plane fitting
Fields of Research : 09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
01 Mathematical Sciences > 0199 Other Mathematical Sciences > 019999 Mathematical Sciences not elsewhere classified
09 Engineering > 0909 Geomatic Engineering > 090903 Geospatial Information Systems
09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering

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