High dynamic range (HDR) imaging enables to immortalize natural scenes similar to the way that they are perceived by human observers. With regular low dynamic range (LDR) capture/display devices, significant details may not be preserved in images due to the huge dynamic range of natural scenes. To minimize the information loss and produce high quality HDR-like images for LDR screens, this study proposes an efficient multi-exposure fusion (MEF) approach with a simple yet effective weight extraction method relying on principal component analysis, adaptive well-exposedness and saliency maps. These weight maps are later refined through a guided filter and the fusion is carried out by employing a pyramidal decomposition. Experimental comparisons with existing techniques demonstrate that the proposed method produces very strong statistical and visual results.

翻译：高动态范围成像(HDR)能够使自然景象与人类观察者所感知的相似,不朽地永久化。由于经常的低动态范围捕捉/播放装置,由于自然景象的动态范围巨大,重要细节可能无法保存在图像中。为了尽量减少信息损失,为LDR屏幕制作高质量的《人类发展报告》图像,本研究提出一种高效的多曝光聚合(MEF)方法,采用简单而有效的重力提取方法,依靠主要组成部分分析、适应性丰富和突出的地图。这些重图后来通过一个有指导的过滤器加以精细化,而聚合则通过使用金字塔分解法进行。与现有技术的实验性比较表明,拟议的方法产生了非常强大的统计和视觉结果。