基于Contourlet变换的多聚焦图像融合

Multifocus Image Fusion Based on Contorlet Transform

由于可见光成像系统的聚焦范围有限，很难获得同一场景内所有物体都清晰的图像，多聚焦图像融合技术可有效地解决这一问题。Contourlet变换具有多尺度多方向性，将其引入图像融合，能够更好地提取原始图像的特征，为融合图像提供更多的信息。该文提出了一种基于区域统计融合规则的Contourlet变换多聚焦图像融合方法。先对不同聚焦图像分别进行Contourlet变换．采用低频系数取平均，高频系数根据区域统计值决定的融合规则。再进行反变换得到融合结果。文中给出了实验结果．并对融合结果进行了分析比较，实验结果表明，该方法能够取得比基于小波变换融合方法更好的融合效果。

Due to the limited depth-of-focus of optical lenses , it is often difficult to get an image that contains all relevant objects in focus. Mulfifocus image fusion method can solve this problem effectively. Contoulet transform has varying directions and multiple scales. When the contourlet transform is introduced to image fusion , the characteristics of original images are taken better and more information for fusion is obtained. A new multifocus image fusion method is proposed in this paper, based on contourlet transform with the fusion rule of region statistics. Different focus images are decomposed using contourlet transform firstly, then low-bands are integrated using the weighted average, high-bands are integrated using region statistics rule. Then the fused image will be obtained by inverse contourlet transform. The experimental results are showed, and compared with the method based on wavelet transform. Experiments show that this approach can achieve better results than the method based on wavelet transform.