Improved Narrow Water Extraction Using a Morphological Linear Enhancement Technique

Abstract

An improved water extraction method using a morphological linear enhancement technique is proposed to improve the delineation of narrow water features for the modified normalized difference water index (MNDWI) derived from remote sensing images. This method introduces a morphological white top-hat (WTH) transforming operation on the MNDWI to extract multi-scale and multidirectional differential morphological profiles and constructs a morphological narrow water index (MNWI). The MNWI can effectively enhance the local contrast of linear objects, allowing narrow water bodies to be easily separated from mountain shadows and other features. Furthermore, to accurately delineate surface water bodies, a dual-threshold segmentation method was also developed by combining an empirical threshold segmentation with the MNDWI for wide water bodies and an automatic threshold segmentation with the MNWI for narrow water bodies. This method was validated using three experimental datasets, which were taken from two different Landsat images. Our results demonstrate that narrow water bodies can be sufficiently identified, with an overall accuracy of over 90%. Most narrow streams or rivers keep a continuous shape in space, and the boundaries of the water bodies are accurately delineated as compared with the MNDWI method. Finally, the proposed method was used to extract the entire inland surface water of Fujian province, China.