Pixel-wise infrared tone remapping for rapid adaptation to high dynamic range variations
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(Published version)
Date
2019
Authors
Griffiths, D.
Scoleri, T.
Brinkworth, R.
Finn, A.
Editors
Hickman, D.L.
Bursing, H.
Bursing, H.
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Conference paper
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Proceedings of SPIE, 2019 / Hickman, D.L., Bursing, H. (ed./s), vol.11159, iss.111590V, pp.1-11
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Electro-Optical and Infrared Systems: Technology and Applications XVI 2019 (11 Sep 2019 - 12 Sep 2019 : Strasbourg, France)
Abstract
Biological vision systems can perform target selection, pattern recognition, and dynamic range adaptation at capability levels far beyond that of human-designed methods. This paper applies a two-stage Biologically-Inspired Vision (BIV) model for image pre-processing and infrared tone remapping, derived from the visual pipeline of the hoverfly. The first stage performs spatially invariant, pixel-wise, intensity normalisation, to intelligently compress scene dynamic range and enhance local contrasts using an adaptive gain control mechanism. The second stage of the model applies adaptive spatio-temporal filtering to reduce redundancy within image sequences. Our experiments demonstrate the strengths of the model on four practical tasks. For large targets, the model acts as a sophisticated edge extractor. The examples show the ability to retrieve the complete structure of a boat from sea clutter, increasing the global contrast factor by 165%. Secondly and thirdly, for small and weak-signature targets, segmentation is demonstrated. A filter is applied to track a 2x2 pixel dragonfly without interruption, and a small maritime vessel, extracted as it passes in front of a larger vessel of similar emissivity. Finally, the power of the BIV model to rapidly compress dynamic range and normalise sudden changes in scene luminance is validated by means of incandescent pyrotechnic pellets launched from an aerial platform.
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Copyright 2019 SPIE