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

Sensors

Wonseok Kang²  Soohwan Yu²  Doochun Seo¹  Jaeheon Jeong¹  Joonki Paik² 

[1] Department of Satellite Data Cal/Val Team, Korea Aerospace Research Institute, 115 Gwahangbo, Yusung-Gu, Daejeon 34133, Korea; E-Mails:;Department of Image, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea; E-Mails:

关键词: destriping;    denoising;    satellite data correction;    combined wavelet-Fourier filter;    non-local means (NLM) filter;   

DOI  :  10.3390/s150922826

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.