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Proceedings Paper

Novel robust rank filters with noise suppression in remote sensing applications
Author(s): Volodymyr I. Ponomaryov; Oleksiy B. Pogrebnyak; Victor Manuel Velasco Herrera
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Paper Abstract

We introduce novel robust filtering algorithms applicable to image and signal processing in the remote sensing applications. They were derived using RM-type point estimators and the restriction technique of the well-known specific for image processing KNN filter. Novel RM-KNN filters effectively remove impulsive noise while edge and fine details are preserved. The proposed filters were tested on simulated images and radar data and were provided excellent visual quality of the processed images and good quantitative quality in the MSE sense over standard median filter. Recommendations to obtain best processing results by proper selection of derived filter parameters are given in this paper. Two derived filters are suitable for impulsive noise reduction in the remote sensing image processing applications. RM-KNN filters can be used as the first stage of image enhancement following by any non-robust techniques such as Sigma-filter on the second stage.

Paper Details

Date Published: 17 August 1998
PDF: 10 pages
Proc. SPIE 3502, Hyperspectral Remote Sensing and Application, (17 August 1998); doi: 10.1117/12.317811
Show Author Affiliations
Volodymyr I. Ponomaryov, Instituto Politecnico Nacional (Mexico)
Oleksiy B. Pogrebnyak, Kharkov Aviation Institute (Mexico)
Victor Manuel Velasco Herrera, Kharkov Aviation Institute (Mexico)


Published in SPIE Proceedings Vol. 3502:
Hyperspectral Remote Sensing and Application
Robert O. Green; Qingxi Tong, Editor(s)

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