针对多聚焦图像融合，本文首先介绍了小波变换融合算法，虽然小波变换方法无冗余，高频分量损失较小，具有较好的融合效果，但存在两个主要缺点：一是移变性，二是融合图像在重构时会受到一些外来因素的影响，所以仍会丢失一些边缘信息，为了克服小波变换法的以上缺点，可以采用基于小波分解和点扩展函数模型PSF相结合的融合方法。该方法首先对不同的图像进行无降2采样的小波分解，以保持与源图像大小相同，然后分别将其各方向、各尺度的高频分量进行叠加，并依此提取其高频分量的特征信息来判定清晰目标或模糊目标，以此来设计融合算法，采用一定的策略将两副源图像进行融合，从而避开了小波的反变换，因此融合后的图像具有比小波变换法更好的融合效果。-multi-focus image fusion, this paper introduces the wavelet transform algorithm, Although the wavelet transform non-redundant, the loss of high-frequency components are smaller, better integration effect, But there are two major drawbacks : First, the shift variability and the second is the integration of image reconstruction will be subject to a number of external factors. Therefore, there would still be some marginal loss of information, in order to overcome the wavelet transform of the above shortcomings, can be used based on wavelet decomposition and the point spread function PSF model combining the fusion method. The first pair of different images ratchet two sampling wavelet decomposition, and to maintain the same source image size. Then all of its direction, the scale of high-freque