Multi-exposure fusion is the common approach to generate high dynamic range (HDR) images that combines multi-exposure images captured for the same scene, but the traditional multi-exposure fusion algorithms lose details in the brightest and darkest regions of the scene. Therefore, many detail enhancement-based exposure fusion algorithms have been proposed to extract these details. However, these algorithms have low efficiency because of the complexity of detail enhancement mechanism, and most of them excessively enhance all the pixels besides of the necessary brightest and darkest pixels. We propose a local detail enhancement mechanism to enhance only the details of brightest and darkest regions by using fast local Laplacian filtering (FLLF). A large number of experiments show that the proposed algorithm has much more high efficiency than the current detail enhancement-based exposure fusion algorithms, and the brightest and darkest details in the high dynamic range scene are preserved well.

多曝光融合是生成高动态范围（HDR）图像的常用方法，该图像结合了为同一场景捕获的多曝光图像，但是传统的多曝光融合算法会丢失场景中最亮和最暗区域的细节。因此，已经提出了许多基于细节增强的曝光融合算法来提取这些细节。然而，由于细节增强机制的复杂性，这些算法效率低下，并且除了必需的最亮和最暗像素之外，大多数算法都过度增强了所有像素。我们提出了一种局部细节增强机制，通过使用快速局部拉普拉斯滤波（FLLF）仅增强最亮和最暗区域的细节。