为了更好地对图像的复杂程度进行描述，先从组成论的角度对传统复杂度的描述方法进行了讨论，并将其引入用于描述图像的复杂度，试图找到一种适合于图像的复杂度描述方法。该文首先讨论了组成论中复杂度的计算方法，并分析了其局限和不足；然后在此基础上，针对图像的特殊性提出从灰度级的出现情况、灰度的空间分布情况、目标对象的出现情况等3个方面，借助信息熵、纹理、边缘等相关因子来描述图像的复杂程度；最后，针对不同复杂程度的遥感图像进行了实验。实验结果表明，该描述方法可以反映出图像的整体复杂程度，并可用于不同图像复杂度的定性和定

In order to describe image complexity in a better way, this paper discussed the description principle of traditional complexity from the perspective of composition theory, and introduced it to the domain of image complexity. Firstly, the authors discussed traditional calculation method of complexity and analyzed its limitation, which is based on a sequence of tests. Secondly, the authors proposed a novel approach to image complexity description, which adopts gray level, gray spatial distribution, and object quantity, including information entropy, texture, edge, and other relevant factors. Finally, the complexity of several different remote sensing images was tested. Results show that this description way can be used to reflect the overall image complexity, achieving the purpose of quantitative and quantitative comparisons between different images.