Abstract: Aiming at multi-spectral image fusion problem, this paper proposes an improved Wavelet-based Contourlet Transform(WBCT) by adopting lifting wavelet transform instead of traditional wavelet transform. Multi-scale decomposition is performed on source images through the improved method to get high-frequency and low-frequency component, which are then processed by different fusion rules and the fused coefficients are obtained. And the inverse improved WBCT is utilized to obtain fused image. Experimental results show that compared with Contourlet transform and lifting wavelet transform, improved method has better integration effect.

Key words: image fusion, Contourlet transforms, Wavelet-based Contourlet Transform(WBCT) method, lifting wavelet transform, spatial frequency, multi-spectral image

摘要： 针对多光谱图像的融合问题，以提升小波变换代替传统小波变换，提出一种改进的WBCT方法。利用该方法对源图像进行多尺度分解，得到高频和低频分量，采用不同的融合规则对其进行处理，得到融合后的系数，并通过逆变换得到融合图像。实验结果表明，与Contourlet变换和提升小波变换相比，改进方法的融合效果有明显提升。

关键词: 图像融合, Contourlet变换, WBCT方法, 提升小波变换, 空间频率, 多光谱图像

CLC Number: 

• TP391.4