Title :
Study on Optimal Wavelet Decomposition Level in Infrared and Visual Light Image Fusion
Author :
Su-xia Xing ; Pei-yuan Guo ; Tian-hua Chen
Author_Institution :
Dept. of Comput. & Inf. Eng., Univ. of Beijing Technol. & Bus., Beijing, China
Abstract :
Wavelet technology in image fusion has a good convergence effect compared with other fusion method. The main impact factors of image fusion effects were wavelet function and wavelet decomposition layers. According to the wavelet transform theory, infrared and visual light images were decomposed 1-5 layers respectively by using different wavelet function; and then under the principle of inverse wavelet transform, fused images were obtained. Finally, the image quality evaluation methods such as information entropy, standard deviation, mutual information, and image fusion quality assessment were used to evaluate the fused images under different decomposition layers. Experimental results show that one layer of wavelet decomposition owns the best results in image fusion.
Keywords :
image fusion; infrared imaging; wavelet transforms; convergence effect; image fusion effects; image fusion quality assessment; information entropy; infrared image fusion; inverse wavelet transform; optimal wavelet decomposition level; standard deviation; visual light image fusion; wavelet decomposition layers; wavelet function layers; wavelet technology; wavelet transform theory; Discrete wavelet transforms; Frequency; Image analysis; Image fusion; Information analysis; Infrared imaging; Mutual information; Principal component analysis; Wavelet analysis; Wavelet transforms; Wavelet transform; decomposition level; image evaluation; image fusion;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.63