SCENIC BEAUTY ESTIMATION
OF
FORESTRY IMAGES
Rising public concern for preserving the beauty of natural
environments and the need to preserve the aesthetic quality of forests
was responsible for the enforcement of various legislative acts to
preserve the beauty of forests. In this talk, a collection of
algorithms developed to extract features for automatically determining
the scenic beauty of a forestry image, and methods employed to relate these
features to the scenic beauty estimate will be presented.
A system using color, density of trees and entropy achieved an error rate
of 36.8%, and a correlation of 0.59 with human judgements.