Novel robust rank filters with noise suppression in remote sensing applications

Volodymyr I. Ponomaryov; Oleksiy B. Pogrebnyak; Victor Manuel Velasco Herrera

doi:10.1117/12.317811

17 August 1998 Novel robust rank filters with noise suppression in remote sensing applications

Volodymyr I. Ponomaryov, Oleksiy B. Pogrebnyak, Victor Manuel Velasco Herrera

Proceedings Volume 3502, Hyperspectral Remote Sensing and Application; (1998) https://doi.org/10.1117/12.317811
Event: Asia-Pacific Symposium on Remote Sensing of the Atmosphere, Environment, and Space, 1998, Beijing, China

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.

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Volodymyr I. Ponomaryov, Oleksiy B. Pogrebnyak, and Victor Manuel Velasco Herrera "Novel robust rank filters with noise suppression in remote sensing applications", Proc. SPIE 3502, Hyperspectral Remote Sensing and Application, (17 August 1998); https://doi.org/10.1117/12.317811

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KEYWORDS

Image filtering

Digital filtering

Image processing

Filtering (signal processing)

Radar

Linear filtering

Remote sensing

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