针对自动对焦技术中存在的全局对焦困难问题，本文提出一种新的基于区域显著性分析的图像融合方法。首先用基于图论的显著性分析(GBVS)算法定位源图像中的聚焦区域，然后使用分水岭和形态学方法进一步处理显著图的封闭区域以去除伪聚焦区域，得到精确提取的聚焦区域；离焦区域用剪切波变换处理后，以SML算子选取有用的细节信息作为融合依据。最后将处理后的聚焦区域和离焦区域融合为全聚焦图像。实验证明，所提出的方法融合图像边缘清晰，细节丰富，视觉效果最好，并且在清晰度和融合度的评价指标上较传统方法提高5%以上。

In the study of autofocus technology, we propose an image fusion method based on saliency analysis, which can solve the problem of all in focus. First, the focal area in the source image is positioned by the graph-based visual saliency (GBVS) algorithm, and then the watershed and morphological methods are used to obtain the closed area of the saliency graph and the pseudo-focus region is removed. The defocused region is processed by the Shearlet transform, and the SML operator is used to choose the fusion parts. Finally, the precise focused region and the processed defocused region are fused into an all in focus image. Experiments show that the fused image of our method is clear and rich in detail, which has the best visual effect, and improves more than 5% in definition and fusion compared with traditional methods.