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M. Chikr El-Mezouar, N. Taleb, K. Kpalma and J. Ronsin, “An IHS Based Fusion for Color Distortion Reduction and Vegetation Enhancement in IKONOS Imagery,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 5, 2011, pp. 1590-1602. doi:10.1109/TGRS.2010.2087029

has been cited by the following article:

• TITLE: Application of Neural Networks to Matlab Analyzed Hyperspectral Images for Characterization of Composite Structures

  AUTHORS: Mahmoud Z. Iskandarani

  KEYWORDS: Hyperspectral; PVT; Image Analysis; Damage Detection; Classification; Neural Networks; WEA

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.5 No.3, July 31, 2013

  ABSTRACT: A novel approach to damage detection in composite structures using hyperspectral image index analysis algorithm with neural network modeling employing Weight Elimination Algorithm (WEA) is presented and discussed. The matrix band based technique allows the monitoring and analysis of a component’s structure based on correlation between sequentially pulsed thermal images. The technique produces several matrices resulting from frame deviation and pixel redistribution calculations with ability for prediction. The obtained results proved the technique to be capable of identifying damaged components with ability to model various types of damage under different conditions.