A Multi-threshold Based Morphological Approach for Extracting Coastal Line Feature in Remote Sensed Images

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 methods is a type of simple but valid methods 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 alongcoastal 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.