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Proceedings Paper

Image fusion based on the self-organizing feature map neural networks
Author(s): Zhaoli Zhang; Sheng-He Sun
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Paper Abstract

This paper presents a new image data fusion scheme by combining median filtering with self-organizing feature map neural networks. The scheme consists of three steps: (1) pre-processing of the images, where weighted median filtering removes part of the noise components corrupting the image, (2) pixel clustering for each image using self- organizing feature map neural networks, and (3) fusion of the images obtained in Step (2), which suppresses the residual noise components and thus further improves the image quality. It proves that such a three-step combination offers an impressive effectiveness and performance improvement, which is confirmed by simulations involving three image sensors.

Paper Details

Date Published: 4 August 2000
PDF: 6 pages
Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395076
Show Author Affiliations
Zhaoli Zhang, Harbin Institute of Technology (China)
Sheng-He Sun, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 4052:
Signal Processing, Sensor Fusion, and Target Recognition IX
Ivan Kadar, Editor(s)

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