Abstract
This paper discusses roles of artificial intelligence in the automatic
interpretation of remotely sensed imagery. We first discuss several
image understanding systems for analyzing complex aerial photographs.
The discussion is mainly concerned with knowledge representation
and control structure in the aerial image understanding systems:
a blackboard model for integrating diverse object detection modules,
a symbolic model representation for three-dimensional object recognition,
and integration of bottom-up and top-down analyses. Then, a model
of expert systems for image processing is introduced that discusses
which and what combinations of image processing operators are effective
to analyze an image. Various information about image processing techniques
is used to find efficient and reliable image analysis processes.
In general, two kinds of knowledge, that is, knowledge about objects
and about analysis tools (i. e., image processing techniques) are
required to realize versatile photointerpretation systems.
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