Space-borne hyperspectral remote sensing imagery noise eliminating based on CFFT self-adapted by optimal SNR

Qingjie Liu; Qizhong Lin; Liming Wang; Qinjun Wang; Fengxian Miao

doi:10.1117/12.910400

15 August 2011 Space-borne hyperspectral remote sensing imagery noise eliminating based on CFFT self-adapted by optimal SNR

Qingjie Liu, Qizhong Lin, Liming Wang, Qinjun Wang, Fengxian Miao

Author Affiliations +

Proceedings Volume 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing; 82030N (2011) https://doi.org/10.1117/12.910400
Event: Seventeenth China Symposium on Remote Sensing, 2010, Hangzhou, China

Abstract

Space-borne hyperspectral remote sensing imagery, supplying both spatial and spectral information for quantitative remote sensing monitoring, is easily polluted by noises from atmosphere, terrain etc. Based on spectral continuum removing and recovering, traditional fast Fourier Transform (FFT) was extended to Continuum Fast Fourier Transform (CFFT) to separate noise from target information in frequency domain (FD). Thus, low-pass filter for reserving useful information was designed for eliminating noise, with its cut-off frequency selected self-adaptively by optimal signal-tonoise ratio (SNR). Hyperion hyperspectral imageries of Beijing and Xinjiang China were singled out for noise removing to validate the filtering ability of the Continuum Fast Fourier Transform self-adapted by Optimal Signal-noise Ratio(CFFTOSNR) method with qualitative description and quantificational indexs, including mean, variance, entropy, definition and SNR etc. Experiment result shows that CFFTOSNR does well in reducing the gauss white noises in spectral domain and stripe and band-subtracting noise in spatial domain respectively, while the quantificational indexs of filtered imagery are all improved, with entropy of post-processed image obviously increased by 5 db.

Citation Download Citation

Qingjie Liu, Qizhong Lin, Liming Wang, Qinjun Wang, and Fengxian Miao "Space-borne hyperspectral remote sensing imagery noise eliminating based on CFFT self-adapted by optimal SNR", Proc. SPIE 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing, 82030N (15 August 2011); https://doi.org/10.1117/12.910400

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Signal to noise ratio

Image filtering

Hyperspectral imaging

Remote sensing

Fourier transforms

Interference (communication)

Absorption

Show All Keywords

Keywords/Phrases

Search In:

Publication Years