A Multi-threshold Based Morphological Approach for Extracting Coastal Line Feature from Remote Sensed Images
一种基于多阈值的形态学提取遥感图象海岸线特征方法

While executing tasks such as sea surveilling, maritime searching and rescue, sea pollution monitoring utilizing remote sensed images, the coastal line feature should be determined at first. Thresholding method is a type of simple but valid method for image segmentation, likewise, they can be used to detect coastal line feature in remote sensed images. However, while conventional thresholding methods used to do it, they are always short of enough discriminating ability to objects' shadow, weak scattering vegetations, dark artificial buildings, sea gulf blurred by noise along costal line. This paper proposes a multi threshold based morphological approach, which divides the isolated regions by thresholding detecting into intra continent, exterior sea, and along coastal isolated regions at first, and then utilizes two definitions and morphological operators to process along coastal regions further so as to improve the detecting accuracy and decreasing false detecting, especially to enhance detecting accuracy for above objects' shadow, vegetations and dark artificial builds. Experiments are executed and the results exhibit the proposed approach possessing better performance than conventional thresholding approach.