针对高分辨率遥感影像中建筑物阴影检测的需求,通过主成分变换和色调、色饱和度和强度(HSI)空间中阴影的光谱特性提取,开展了基于阴影概率约束的阴影检测方法研究。根据主成分变换结果与地物在HSI空间光谱特性的差异,消除暗色地物的影响,并用阴影概率检测存在于水体中的建筑物阴影,避免了传统方法由于水体与建筑物阴影光谱特征相近而引起的误检和漏检现象。基于吉林一号卫星影像的实验结果证明,所提方法的误检率和漏检率低于6%,总体分类精度和Kappa系数高于0.9,水体对阴影检测结果的影响明显降低,影像中阴影的整体检测效果得到提升。

In order to meet the needs of building shadow detection in high resolution remote sensing images, we study the shadow detection method based on shadow probability constraint by principal component transformation and spectral feature extraction in hue, saturation, and intensity (HSI) space. Based on the results of principal component transformation and the difference of the spectral characteristics of ground objects in HSI space, we eliminate the influence of dark objects and detect the shadow of buildings in the water using shadow probability. Compared with traditional methods, the proposed method avoids the false detection and missed detection caused by the similar spectral characteristics of water bodies and buildings. Experimental results based on Jilin No.1 images show that the false detection rate and missed detection rate of the proposed method are less than 6%, the overall classification accuracy and Kappa coefficient are higher than 0.9, the impact of water on shadow detection results is reduced, and the overall effect of image shadow detection is improved.