Shadow Detection and Removal from Remote Sensing Images using NDI and Morphological Operators
Shadow Detection and Removal from Remote Sensing Images using NDI and Morphological Operators
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DOI：
10.5120/5731-7805
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发表时间：
2012-03
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影响因子：
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通讯作者：
Krishna Kant Singh;Kirat Pal;Madhav J. Nigam
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文献类型：
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作者：
Krishna Kant Singh;Kirat Pal;Madhav J. Nigam
在遥感图像中，由于被抬高的物体会产生阴影。阴影对城市中建筑物、塔楼等图像特征的正确提取造成了障碍，也可能导致目标的虚假色调和形状失真，从而降低图像质量。因此，分割阴影区域并恢复它们的信息对于图像解释是重要的。针对复杂城市彩色遥感影像中阴影的存在，提出了一种基于HSV颜色模型的阴影检测与去除方法。该方法首先利用归一化差分指数和基于大津法的阈值分割检测阴影。一旦阴影被检测到，它们被分类，并使用形态学算子估计每个阴影周围的非阴影区域称为缓冲区。这些缓冲区的均值和方差用于补偿阴影区域。
Shadows appear in remote sensing images due to elevated objects. Shadows cause hindrance to correct feature extraction of image features like buildings ,towers etc. in urban areas it may also cause false color tone and shape distortion of objects, which degrades the quality of images. Hence, it is important to segment shadow regions and restore their information for image interpretation. This paper presents an efficient and simple approach for shadow detection and removal based on HSV color model in complex urban color remote sensing images for solving problems caused by shadows. In the proposed method shadows are detected using normalized difference index and subsequent thresholding based on Otsu’s method. Once the shadows are detected they are classified and a non shadow area around each shadow termed as buffer area is estimated using morphological operators. The mean and variance of these buffer areas are used to compensate the shadow regions.