Least square fitting of pollock model for tree detection and crown delineation
2017
Pollock model was one of the popular template matching algorithms, which constructs a three-dimensional description of each individual tree-crown envelope. Unfortunately, it is always challenging to determine parameters since each tree has different grown condition. This paper proposed an iterative least square fitting algorithm to form a Pollock model best fitting each individual tree for tree detection and crown delineation. The proposed algorithm provides a solution to avoid difficulties of finding the best set of parameters for each tree crown. As a result, it improves the detection rate and decreases the computing time as shown in the experimental studies. The proposed least square fitting algorithm is more suitable for practical applications.
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