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Proceedings Paper

Multispectral image fusion based on diffusion morphology for enhanced vision applications
Author(s): Vladimir A. Knyaz; Oleg V. Vygolov; Yury V. Vizilter; Sergey Y. Zheltov; Boris V. Vishnyakov
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Paper Abstract

Existing image fusion methods based on morphological image analysis, that expresses the geometrical idea of image shape as a label image, are quite sensitive to the quality of image segmentation and, therefore, not sufficiently robust to noise and high frequency distortions. On the other hand, there are a number of methods in the field of dimensionality reduction and data comparison that give possibility of avoiding an image segmentation step by using diffusion maps techniques. The paper proposes a new approach for multispectral image fusion based on the combination of morphological image analysis and diffusion maps theory (i.e. Diffusion Morphology). A new image fusion algorithm is described that uses a matched diffusion filtering procedure instead of morphological projection. The algorithm is implemented for a three channels Enhanced Vision System prototype. The comparative results of image fusion are shown on real images acquired in flight experiments.

Paper Details

Date Published: 17 May 2016
PDF: 8 pages
Proc. SPIE 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII, 984022 (17 May 2016); doi: 10.1117/12.2224086
Show Author Affiliations
Vladimir A. Knyaz, GosNIIAS (Russian Federation)
Oleg V. Vygolov, GosNIIAS (Russian Federation)
Yury V. Vizilter, GosNIIAS (Russian Federation)
Sergey Y. Zheltov, GosNIIAS (Russian Federation)
Boris V. Vishnyakov, GosNIIAS (Russian Federation)


Published in SPIE Proceedings Vol. 9840:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII
Miguel Velez-Reyes; David W. Messinger, Editor(s)

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