New Zealand Journal of Agricultural Research abstracts

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Fusion algorithm for multi-sensor images based on PCA and lifting wavelet transformation

Li Mingxi^1,2,*

Mao Hanping¹

Zhang Yancheng^{1, 3}

Wang Xinzhong¹

¹Provincial Key Laboratory of Modern Agricultural Equipment and Technology
Jiangsu University
Zhenjiang City
212013, PR China

²Edit Department of Journal
Huang-shi Institute of Technology
Huang-shi City
435003, PR China

³College of Engineering and Technology
Yunnan Agricultural University
Kunming City
650201, PR China

^*Author for correspondence: limx10920@yahoo.com.cn

Abstract A novel fast image fusion scheme based on principal component analysis (PCA) and lifting wavelet transformation (LWT) is proposed. Firstly, the principal component images of the registered original colour image are obtained by PCA transformation. Then, the first principal component image and near infrared imagery are merged using lifting wavelet transformation (LWT) based on regional features. The fused image replaces the first principal component of the visual colour image. Finally, the final composite image is obtained by inverse PCA transformation. Compared with other fusing algorithms, the experimental results demonstrate that this fusion scheme is more effective in fusing image quality than the traditional PCA or wavelet transformation fusion methods. The obtained image conforms to human vision features. The ­standard deviation (σ) and average gradients (g) are a little smaller with this fusion algorithm than the wavelet transformation method, but they are bigger with this fusion algorithm than the PCA method; however, entropy (EN) and correlation coefficients are larger with this fusion algorithm than with the PCA or wavelet transformation method. The fusion image contains more information and stronger spatial detail performance. The merged image is more advantageous to be further analysed, understood and recognised.

Keywords image fusion; lifting wavelet transforms; multi-sensor images; principal component analysis

A07076; Online publication date 17 December 2007; Received and accepted 10 August 2007

New Zealand Journal of Agricultural Research, 2007, Vol. 50: 667–671
0028–8233/07/5005–0667 © The Royal Society of New Zealand 2007

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