简要地回顾了数据融合技术产生，发展的必然性，以及学者们提出的几种相关定义；尽可能详细地分析了数据融合的框架结构。包括像素层，特征层和决策层三层数据融合，并重点分析了各个数据融合层中的融合方法，以及这些方法在遥感图象处理中的应用，由于数据融合与遥感图象分类，目标检测，变化检测，目标识别的密切相关性，还对数据融合与这些应用的结合作了一定的分析。最后给出了结论和展望。

Data fusion is a powerful tool to process tremendous remote sensing data for its capability to combine useful information of multisource or multitemporal data, and eliminate their redundancy, so it has been applied on many areas extensively, especially, on remote sensing image processing. At first, this paper simply reviews the necessity of data fusion's appearance and development, together with several definitions brought forward by several investigators. Afterwards, this paper not only attempts to analyze the Data Fusion Engine framework and configuration comprising of pixels-level?feature-level and decision-level fusions detailedly, but also principally analyze the fusion methods and their applications of each data fusion level. In addition, because of close relation between data fusion and image classification, object detection, change detection, and target recognition, these data fusion based applications are also analyzed briefly. Finally, summary and prospect are described.