Optimal Number of Decomposition Levels for Fusion of Different Landscape Images

  • 1. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China;
    2. Guangdong Institute of Eco-environment and Soil Sciences, Guangzhou 510650, China

Received date: 2011-03-23

  Revised date: 2011-06-07

  Online published: 2011-08-23


The joint use of IHS and wavelet transforms is a popular fusion method to incorporate multi-spectral remote data and high-resolution panchromatic data. However, some important factors have been directly neglected when this method is adopted. In these factors, number of decomposition levels is the key to influence the effect of the fusion images, and the problem about how to choose the optimal number of decomposition level according to remote images with different landscape characteristics should be focused on. In this paper, SPOP panchromatic data with 2.5×2.5m and TM mutli-spectral data with 30×30 m were used, entropy, average gradient and correlation coefficients were calculated as the evaluation indices for fusion images. The object of this paper was to explore the response of fusion images performances from different landscape characteristics to the choice of number of decomposition levels, and according to those results from the fusion treatments we found the optimal number of the levels to the given remote images. The results showed that the performances of fusion images had a close relationship with land-cover information and landscape types included in the remote images obviously. Entropy of different landscape images displayed very strong variance with changing decomposition levels, but those with correlation coefficients were slight. Comparing with other types of remote images, forest landscape images showed the most sensitive relationship with number of decomposition levels. Different indices exhibited different characteristics to decomposition levels, and images with different landscape information had their specific critical decomposition levels. According to the analysis given above, the optimal number of the levels to a given remote image could be confirmed. For example, five was the optimal number of the levels of urban landscape image. With this choice, fusion image exhibited the best performance in three evaluation indices. This paper tries to provide helpful information when we use the integration of wavelet transforms and IHS as the method in multiple sources remotely sensed data fusion.

Cite this article

GUO Guanhua, CHEN Yingbiao, WU Zhifeng, WEI Jianbing . Optimal Number of Decomposition Levels for Fusion of Different Landscape Images[J]. Journal of Geo-information Science, 2011 , 13(4) : 556 -561 . DOI: 10.3724/SP.J.1047.2011.00556


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