In this paper a general approach based on morphological connected filters for the spatial simplification of very high resolution remote sensing images is introduced. In greater detail, the proposed approach is made up of two steps: i) the selection of the parameters defining the connected filters driven by the information available on the scene and on the specific application; and ii) the application of the tuned filter to the input image. This work aims at: i) explicitly delineating the characteristic of an approach for the spatial simplification of images based on connected filters; ii) defining a general architecture suitable for the analysis in different scenarios modeling common different operative conditions; iii) giving guidelines for the automation of the simplification process according to different operational settings; iv) qualitatively evaluating the application of the proposed approach on a real data set in different scenarios.

A general approach to the spatial simplification of remote sensing images based on morphological connected filters

Dalla Mura, Mauro;
2011-01-01

Abstract

In this paper a general approach based on morphological connected filters for the spatial simplification of very high resolution remote sensing images is introduced. In greater detail, the proposed approach is made up of two steps: i) the selection of the parameters defining the connected filters driven by the information available on the scene and on the specific application; and ii) the application of the tuned filter to the input image. This work aims at: i) explicitly delineating the characteristic of an approach for the spatial simplification of images based on connected filters; ii) defining a general architecture suitable for the analysis in different scenarios modeling common different operative conditions; iii) giving guidelines for the automation of the simplification process according to different operational settings; iv) qualitatively evaluating the application of the proposed approach on a real data set in different scenarios.
2011
9781457710032
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/51406
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