Abstract
Automatic interpretation of digital images is a difficult task.
In this paper, we have proposed knowledge based approach for
Landsat image segmentation and interpreted without any prior
image dependent information. It includes an integration of
image processing techniques, knowledge from domain experts
and ancillary information such as previous maps of the study
area. We discuss three important issues in automatic digital
image interpretation are image registration, road detection and
knowledge based segmentation. In this study, major land cover
types are organized in a hierarchical structure. A complete
knowledge based segmentation technique may consist of two
stages. The first stage uses the proposed method to segment a
Landsat image by spectral knowledge rules. The second stage
then collects more area dependent spatial rules and the prior
map information to perform a complete segmentation. Nagao
and Mastuyama have developed a knowledge-based system,
which performs a structural analysis of complex aerial
photographs using a technique called segmentation-byrecognition..
One advantage of this method is its flexibility in
applying it to geo graphically different areas. This work
develops techniques for automating the process of IRS LISS-III
image interpretation. The experimental results show that
the proposed method can be successful in segmenting
complicated Landsat image. Through this study, we
believe that the proposed hierarchical method is a
promising approach for Landsat image segmentation. In
order to make the proposed method more reliable and powerful,
in future research topics, these are being incorporated.
AbstractAutomatic interpretation of digital images is a difficult task.In this paper, we have proposed knowledge based approach forLandsat image segmentation and interpreted without any priorimage dependent information. It includes an integration ofimage processing techniques, knowledge from domain expertsand ancillary information such as previous maps of the studyarea. We discuss three important issues in automatic digitalimage interpretation are image registration, road detection andknowledge based segmentation. In this study, major land covertypes are organized in a hierarchical structure. A completeknowledge based segmentation technique may consist of twostages. The first stage uses the proposed method to segment aLandsat image by spectral knowledge rules. The second stagethen collects more area dependent spatial rules and the priormap information to perform a complete segmentation. Nagaoand Mastuyama have developed a knowledge-based system,which performs a structural analysis of complex aerialphotographs using a technique called segmentation-byrecognition..One advantage of this method is its flexibility inapplying it to geo graphically different areas. This workdevelops techniques for automating the process of IRS LISS-IIIimage interpretation. The experimental results show thatthe proposed method can be successful in segmentingcomplicated Landsat image. Through this study, webelieve that the proposed hierarchical method is apromising approach for Landsat image segmentation. Inorder to make the proposed method more reliable and powerful,in future research topics, these are being incorporated.
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