基于改进引导滤波和量子遗传算法的图像融合

An Image Fusion Method Based on Improved Guided Filtering and Quantum Genetic Algorithm

为了有效解决图像融合中存在的光谱失真和空间细节信息缺失问题,提出一种基于改进引导滤波和量子遗传算法的图像融合方法。首先对多光谱图像进行上采样,并采用改进引导滤波对全色图像进行拟合处理,然后选用量子遗传算法对新的全色图像进行优化。依据小波变换法分别对多光谱图像和全色图像展开分解,选取高频部分进行加权平均融合,低频部分采用像素取大原则,最后通过小波逆变换得到融合图像。实验结果表明,改进方法能够有效提升图像的平均梯度、信息熵等指标,使得融合图像的光谱失真现象得到改善,边缘细节信息得到增强,视觉效果良好。

To solve the problems of spectral distortion and lack of spatial details in image fusion an image-fusion approach was proposed based on the improved guided filtering and quantum genetic algorithm.Firstly up-sampling operation was used in multi-spectral image and the panchromatic image was fitted by the improved guided filtering.Secondly the new panchromatic image was optimized by using quantum genetic algorithm.Next the multi-spectral image and panchromatic image were decomposed by wavelet transform.Then weighted average was made to the high-frequency part and the principle of selecting the maximum-pixel was used to the low-frequency part.Finally the fusion image was reconstructed by adopting the inverse wavelet transformation.Experimental results show that the improved method effectively increases such image indicators as average gradient and information entropy which can enhance the details and spectral information in image fusion and get better visual effect.