Methods to Combine Multiple Images to Improve Quality

Methods to Combine Multiple Images to Improve Quality

Anders. P. Kaestner

Abstract. Noise and artifacts have a negative impact on the image quality and the resulting image analysis. The signal to noise ratio (SNR) caused by the neutron flux and the light conversion efficiency is one component in this. Here, we are more concerned about the effect of outliers, which frequently appear in neutron images. There are two approaches to reduce the impact of outliers (1) by applying spatial outlier rejection filters on each image and (2) by acquiring multiple images which are combined into a single image with a total neutron dose similar to the dose of the image in option (1). Here, we focus on the second option where we will show the importance of the choice of combination method. The impact is demonstrated to show the ability to reject outliers but also that the SNR can be improved. The image combination approach has the advantage that it does not affect neighbor pixels or larger regions. The tested methods are the arithmetic average, median, and a new weighted average. The weighted average shows promising results compared to the other two alternatives both regarding improving SNR and its outlier rejection ability.

Keywords
Outliers, Image Combination, Neutron Imaging

Published online 1/5/2020, 5 pages
Copyright © 2020 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Anders. P. Kaestner, Methods to Combine Multiple Images to Improve Quality, Materials Research Proceedings, Vol. 15, pp 193-197, 2020

DOI: https://doi.org/10.21741/9781644900574-30

The article was published as article 30 of the book Neutron Radiography

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

References
[1] Hungler, P.; Bennett, L.; Lewis, W.; Bevan, G.; Metzler, J. Comparison of Image Filters for Low Dose Neutron Imaging. Physics Procedia 2013, 43, 169–178. https://doi.org/10.1016/j.phpro.2013.03.020
[2] Li, H.; Schillinger, B.; Calzada, E.; Yinong, L.; Muehlbauer, M. An adaptive algorithm for gamma spots removal in CCD-based neutron radiography and tomography. Nuclear Instruments & Methods in Physics Research Section A 2006, 564, 405–413. https://doi.org/10.1016/j.nima.2006.04.063
[3] Weisstein, E.W. CRC Concise Encyclopedia of Mathematics, Second Edition; Chapman and Hall/CRC, 2002. https://doi.org/10.1201/9781420035223
[4] Kaestner, A. MuhRec – a new tomography reconstructor. Nuclear Instruments and Methods A 2011, 212 651, 156–160. https://doi.org/10.1016/j.nima.2011.01.129