A detail preserving multi-exposure image fusion algorithm was proposed to address the problem of the loss of visual details and ghost artifacts in traditional multi-exposure images. Firstly, three image features, image details, exposure brightness and color information, were calculated. In which, the image details were obtained by using a guided filter, the each exposure intensity was weighted by a Gaussian function and the color information was measured by color saturation. Then, the difference maps and correlation coefficients were used to detect the motion objects in dynamic scenes and the focused weight map of static and dynamic scenes were calculated respectively by using feature indexes and detection results. In order to remove the noise effect, a recursive filter was used to correct the focused weight image, and the focused image was obtained by a pixel-by-pixel weighted sum of the input images. Ten kinds of multi-exposure image sequences were tested in the experiments and obtained results were compared with that of six kinds of traditional methods. The experimental results demonstrate that the proposed algorithm exhibits good visual appearance and preserves more details. It also effectively removes ghost artifacts in dynamic scenes. It concludes that the proposed algorithm is better than 6 classical methods and it produces desirable images in both static scenes and dynamic scenes.