High-resolution satellite images contain a huge
amount of information. Shadows in such images generate real
problems in classifying and extracting the required information.
Although signals recorded in shadow area are weak, it is still
possible to recover them. Significant work is already done in
shadow detection direction but, classifying shadow pixels from
vegetation pixels correctly is still an issue as dark vegetation
areas are still misclassified as shadow in some cases. In this letter,
a new image index is developed for shadow detection employing
multiple bands. Shadow pixels are classified from the index
histogram by an automatic threshold identification procedure.
The whole approach is applied on different study areas and high
accuracies are achieved (average of 97%). The linear correlation
method is then applied to compensate the classified shadow pixels.
Two standard approaches of shadow detection are then applied
to the same study areas to validate the proposed approach. The
results show that the proposed approach achieves the best results.
It also gives robust shadow detection results in classifying shadow
from vegetation pixels comparable to the other two considered
standard approaches.