针对同一场景多聚焦图像的融合问题，提出了一种基于方向区域特性的Contourlet域多聚焦图像融合算法.该算法对图像进行Contourlet变换，分解为不同尺度、不同方向的高低频子带；低频和高频子带分别采用方向区域的方差匹配度和能量作为融合规则；最后通过反变换得到融合图像.结果表明，所提出的方向区域方法能够更好地体现二维图像中的曲线或直线状边缘特征，是一种有效可行的图像融合算法.

Utilizing the contourlet′s advantages of multiscale, localization, directionality and anisotropy, a multifocus image fusion algorithm based on directional windows statistics in contourlet domain is developed. Source images are firstly decomposed to the domain of the contourlet transform, then the image fusion is implemented in subbands with different scale and direction combining with region statistics. Regional variance and local energy are adopted as fusion rules in lowpass and highpass subbands, respectively. And the fused image is obtained through inverse transform. Compared to traditional gradient pyramid algorithm and wavelet based algorithm, experimental results show that the directional windows method can detect image features more effectively and the fused image has better subjective visual effect.