摘要：人类视觉系统对于图像的局部对比度非常敏感，如果把小波变换和方向对比度结合起来，融合效果可能更好。在研究了方向对比度后提出了一种新的基于小波方向对比度的多聚焦图像融合方法。首先对参加融合的两幅图像进行小波多尺度分解，然后在每幅图像的每个分解层上，分别计算高频子带每个像素的邻域均值和低频子带的邻域均值之比，其中该分解层的低频子带是由上个分解层的低频子带和高频子带求2维离散小波逆变换得到，采用两者之比较大者所对应的高频子带系数作为融合后对应的小波系数，然后从最高分解层到最低分解层依次对得到的高频小波系数和该分解层的低频小波系数求2维离散小波逆变换，最终得到融合后的图像。这种方法考虑了邻域内像素的相关性，减少了融合像素的错误选取。实验结果表明，该方法的融合效果比针对每个像素求小波方向对比度的多聚焦图像融合方法的融合效果得到提高。

Abstract：The vision system of human being is sensitive to local contrast. If the wavelet transform and directional contrast are put together, the effect of image fusion may be better. This paper puts forward a new multi-focus image fusion scheme based on wavelet directional contrast after researching the directional contrast. First, the input multi-focus images are decomposed by wavelet transform. Second, the high frequency neighborhood and low frequency neighborhood are ratioed on each disaggregatire layer of each image. Low frequency of this decomposition is obtained by two-dimensional discrete wavelet inverse transform of last decomposition’s low frequency and high frequency. The bigger ratio one corresponding high frequency wavelet coefficient is taken to corresponding wavelet coefficient. Then two-dimensional discrete wavelet inverse transform of high frequency and low frequency from the maximum decomposition to minimum decomposition is calculated. The fusion image is acquived at last. The neighborhood relativity of pixel is taken into account, the error in selecting pixels is reduced. Experiments show that this scheme is improved than the multi-focus image scheme calculating the wavelet directional contrast of each pixel.