Multispectral image fusion based on diffusion morphology for enhanced vision applications

Vladimir A. Knyaz; Oleg V. Vygolov; Yury V. Vizilter; Sergey Y. Zheltov; Boris V. Vishnyakov

doi:10.1117/12.2224086

17 May 2016 Multispectral image fusion based on diffusion morphology for enhanced vision applications

Vladimir A. Knyaz, Oleg V. Vygolov, Yury V. Vizilter, Sergey Y. Zheltov, Boris V. Vishnyakov

Proceedings Volume 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII; 984022 (2016) https://doi.org/10.1117/12.2224086
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

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.

Citation Download Citation

Vladimir A. Knyaz, Oleg V. Vygolov, Yury V. Vizilter, Sergey Y. Zheltov, and Boris V. Vishnyakov "Multispectral image fusion based on diffusion morphology for enhanced vision applications", Proc. SPIE 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII, 984022 (17 May 2016); https://doi.org/10.1117/12.2224086

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