为突出多光谱遥感图像中的构造信息， 提出了用主成分分析、 最大噪声变换和原始数据联合进行信息增强的方法。 首先对原始数据进行主成分分析和最大噪声变换， 然后对变换结果与原始数据进行归一化处理的基础上进行波段选择， 最后进行假彩色合成并输出结果。 利用新疆哈图地区的ETM数据进行构造增强的效果表明， 该方法不仅丰富了遥感图像的颜色、 拉大了不同类地物间的色彩差异， 为提取不同类地物信息提供了一条有效的途径， 而且还有力增强了宏观构造、 凸现了小构造和肠状构造， 为展现研究区构造格局、 建立遥感找矿模式提供了一套行之有效的方法。

Based on the principle of mineral generation, structures could provide not only passage ways for ore-forming fluid, but also space for them to aggregate. So, it was very important to study the feature of structures in study area before mineral exploration. In order to highlight structures using multispectral remote sensing data, an algorithm integrating principle component analysis (PCA), maximum noise fraction transformation (MNF) and original image data was proposed here. In the algorithm, the original image was firstly transformed by PCA and MNF; then all bands were normalized to reduce errors caused by different band dimensions, and three bands containing detailed structure information were selected to form the false color image in which structures in study area were highlighted. Results of transformation on enhanced thematic mapper (ETM) data acquired on June 27th 2000 in Hatu area, Xinjiang province, China showed that (1) the transformed image was not only more colorful than the original data, but also more gradational than the original data. (2) The color difference among objects was enhanced by the algorithm. (3) Structrues were highlighted by the algorithm. Therefore, the algorithm’s effect of highlighting structures in study area was noticeable.