Image fusion based on the self-organizing feature map neural networks

Zhaoli Zhang; Sheng-He Sun

doi:10.1117/12.395076

4 August 2000 Image fusion based on the self-organizing feature map neural networks

Zhaoli Zhang, Sheng-He Sun

Proceedings Volume 4052, Signal Processing, Sensor Fusion, and Target Recognition IX; (2000) https://doi.org/10.1117/12.395076
Event: AeroSense 2000, 2000, Orlando, FL, United States

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.

Citation Download Citation

Zhaoli Zhang and Sheng-He Sun "Image fusion based on the self-organizing feature map neural networks", Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); https://doi.org/10.1117/12.395076

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