Adaptive IR and VIS image fusion

Adaptive image fusion system based on neural network principle was realized. It works with digitalized video sequences of visible and infrared band sensors, and is able to produce the optimal fused image for a wide range of lighting conditions through an adaptive change of a fusion algorithm. The change is driven by a change in the measured statistic of the input images. The best algorithm for a particular input is found with the help of an objective measurement of the fusion process quality.

[1]  Timothy F. Cootes,et al.  Objectively adaptive image fusion , 2007, Inf. Fusion.

[2]  Ling Yang,et al.  An Adaptive Image Fusion Method Based on Local Statistical Feature of Wavelet Coefficients , 2009, 2009 International Symposium on Computer Network and Multimedia Technology.

[3]  D. M. Ryan,et al.  Night pilotage assessment of image fusion , 1995, Defense, Security, and Sensing.

[4]  A. Bovik,et al.  A universal image quality index , 2002, IEEE Signal Processing Letters.

[5]  Zheng Liu,et al.  Context enhancement through infrared vision: a modified fusion scheme , 2007, Signal Image Video Process..

[6]  杨波,et al.  Review of Pixel-Level Image Fusion , 2010 .

[7]  Moira I. Smith,et al.  Image fusion of II and IR data for helicopter pilotage , 2000, SPIE Optics + Photonics.

[8]  G. Piella New quality measures for image fusion , 2004 .

[9]  Alexander Toet,et al.  Fusion of visible and thermal imagery improves situational awareness , 1997 .

[10]  Nikolaos Mitianoudis,et al.  Adaptive Image Fusion Using Ica Bases , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.