Spectral-based multi-level Morphological Active Contour algorithm for individual tree detection and crown delineation

Multi-level Morphological Active Contour algorithm (MMAC) had been proposed to effectively increase recognition rate of individual tree in mountainous areas. However, it was specifically designed for LiDAR CHM data only, which make the algorithm incompatible with any other type of remote sensing data. To relieve constraints of MMAC this manuscript proposed a spectral-based MMAC (SB-MMAC), which retains the framework of MMAC by replacing height information from LiDAR CHM model with spectral information from multispectral images. The proposed SB-MMAC is comprised of two stages, seed blobs detection and modified active contour model. The experimental study further demonstrated the utility of SB-MMAC.