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Sensors 2015, 15(9), 22826-22853; doi:10.3390/s150922826

Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering

1
Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea
2
Department of Satellite Data Cal/Val Team, Korea Aerospace Research Institute, 115 Gwahangbo, Yusung-Gu, Daejeon 34133, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Assefa M. Melesse
Received: 22 April 2015 / Revised: 28 July 2015 / Accepted: 1 September 2015 / Published: 10 September 2015
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [4614 KB, uploaded 10 September 2015]   |  

Abstract

In very high-resolution (VHR) push-broom-type satellite sensor data, both destriping and denoising methods have become chronic problems and attracted major research advances in the remote sensing fields. Since the estimation of the original image from a noisy input is an ill-posed problem, a simple noise removal algorithm cannot preserve the radiometric integrity of satellite data. To solve these problems, we present a novel method to correct VHR data acquired by a push-broom-type sensor by combining wavelet-Fourier and multiscale non-local means (NLM) filters. After the wavelet-Fourier filter separates the stripe noise from the mixed noise in the wavelet low- and selected high-frequency sub-bands, random noise is removed using the multiscale NLM filter in both low- and high-frequency sub-bands without loss of image detail. The performance of the proposed method is compared to various existing methods on a set of push-broom-type sensor data acquired by Korean Multi-Purpose Satellite 3 (KOMPSAT-3) with severe stripe and random noise, and the results of the proposed method show significantly improved enhancement results over existing state-of-the-art methods in terms of both qualitative and quantitative assessments. View Full-Text
Keywords: destriping; denoising; satellite data correction; combined wavelet-Fourier filter; non-local means (NLM) filter destriping; denoising; satellite data correction; combined wavelet-Fourier filter; non-local means (NLM) filter
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kang, W.; Yu, S.; Seo, D.; Jeong, J.; Paik, J. Push-Broom-Type Very High-Resolution Satellite Sensor Data Correction Using Combined Wavelet-Fourier and Multiscale Non-Local Means Filtering. Sensors 2015, 15, 22826-22853.

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