Infrared Image Mosaic Based on Pulse Coupled Neural Network

Abstract:

According to the infrared image noise interference serious and low signal to noise ratio characteristics, an image mosaic algorithm based on pulse coupled neural network is presented in this paper. The algorithm uses the PCNN imitation of biological vision to extract edge information, adopts the Hausdorff distance as the registration similarity measure, afterwards, computes the optimal registration parameters, simultaneously, uses the weighted average fusion method to achieve image mosaic. The experimental results show that the algorithm can achieve precise image mosaic and have better robustness to noise.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2493-2497
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2493
• Online since: December 2012
• Authors: Xue Wu Zhang, Yan Wang, Wei Li, Yun Zhou
• Keywords: Edge Detection, Hausdorff Measure, Image Processing, Infrared Image Mosaic, Pulse Coupled Neural Network

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