Cloud and Cloud-Shadow Detection in SPOT5 HRG Imagery with Automated Morphological Feature Extraction
Cloud and Cloud-Shadow Detection in SPOT5 HRG Imagery with Automated Morphological Feature Extraction
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DOI：
10.3390/rs6010776
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发表时间：
2014-01-01
期刊：
影响因子：
5
通讯作者：
Fisher, Adrian
中科院分区：
文献类型：
--
作者：
Fisher, Adrian
随着数据可用性的增加，检测卫星图像中的云变得越来越重要，但是许多地球观测传感器并不是为这项任务而设计的。在地球观测卫星 5 (SPOT5) 高分辨率几何 (HRG) 图像中，在四个可用波段（绿色、红色、近红外和短波红外）中，云的反射特性与地球表面的常见特征非常相似。这里介绍的方法称为 SPOTCASM（SPOT 云和阴影掩蔽），通过使用一系列新颖的图像处理步骤来解决这个问题，并且是第一个专门为 SPOT5 HRG 图像开发的云掩蔽方法。它首先使用图像特定阈值检测标记像素，然后使用标记分水岭变换从这些标记中生长片段。阈值定义为图像表面反射率值的二维直方图中的线，由两个波段计算得出。使用太阳和卫星角度以及云和阴影物体面积之间的相似性来测试其有效性。 SPOCASM 在澳大利亚新南威尔士州 (NSW) 的 313 张阴天图像档案中进行了测试，其中 95% 的图像的总体准确率超过 85%。由于假云（例如高反射地面）和假阴影（例如深色水体）导致的委托误差可能很高，由于与底层地表非常相似的薄云导致的遗漏误差也可能很高。通过手动编辑可以快速减少这些错误，这是目前在实施 SPOCASM 的操作环境中采用的方法。该方法被用来掩盖新南威尔士州不断扩大的图像档案中的云和阴影，从而促进环境变化检测。
Detecting clouds in satellite imagery is becoming more important with increasing data availability, however many earth observation sensors are not designed for this task. In Satellite pour l'Observation de la Terre 5 (SPOT5) High Resolution Geometrical (HRG) imagery, the reflectance properties of clouds are very similar to common features on the earth's surface, in the four available bands (green, red, near-infrared and shortwave-infrared). The method presented here, called SPOTCASM (SPOT cloud and shadow masking), deals with this problem by using a series of novel image processing steps, and is the first cloud masking method to be developed specifically for SPOT5 HRG imagery. It firstly detects marker pixels using image specific threshold values, and secondly grows segments from these markers using the watershed-from-markers transform. The threshold values are defined as lines in a 2-dimensional histogram of the image surface reflectance values, calculated from two bands. Sun and satellite angles, and the similarity between the area of cloud and shadow objects are used to test their validity. SPOTCASM was tested on an archive of 313 cloudy images from across New South Wales (NSW), Australia, with 95% of images having an overall accuracy greater than 85%. Commission errors due to false clouds (such as highly reflective ground), and false shadows (such as a dark water body) can be high, as can omission errors due to thin cloud that is very similar to the underlying ground surface. These errors can be quickly reduced through manual editing, which is the current method being employed in the operational environment in which SPOTCASM is implemented. The method is being used to mask clouds and shadows from an expanding archive of imagery across NSW, facilitating environmental change detection.