Quickbird全色与多光谱数据融合算法的比较

Comparison of Fusion Algorithms of IKONOSPAN and Multi-spectral Images

以Quickbird全色和多光谱数据为例,采用Brovey变换、高通滤波(HPF)变换、主成分(PCA)变换、主成分替换小波变换算法对比研究了同一传感器全色和多光谱数据的融合问题。以均值、标准差、信噪比、信息熵、平均梯度、相关系数及偏差指数为客观融合质量评价指标,由定性和定量的分析认为:针对Quickbird数据而言,综合考虑光谱保真性、信息量和清晰度,PCA变换是最佳的融合算法,而主成分替换小波法要优于Brovey变换和HPF变换,从而筛选出比较适合Quickbird数据的融合方法。

In this paper,four different fusion algorithms such as Brovey,HPF,PCA and PCA replacement of wavelet transform were comparaed when the panchromatic and multi-spectral images of Quickbird were merged.It used average,Singal-to-Noise,information entropy,clarity and correlation to evaluate the quality of fusion.With consideration of the spectral information fidelity,information content and the improvement of spatial detail information,the experiment indicated that PCA was the best fusion alorithm and PCA replacement of wavelet transform was better than Brovey and HPF,and we selected suitable Quickbird data fusion method.