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Remote Sens. 2018, 10(1), 79;

A Novel Method to Remove Fringes for Dispersive Hyperspectral VNIR Imagers Using Back-Illuminated CCDs

Key Laboratory of Infrared System Detection and Imaging Technologies, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
University of Chinese Academy of Sciences, Beijing 100049, China
Qidong Optoelectronic Remote Sensing Center, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Qidong 226200, China
Author to whom correspondence should be addressed.
Received: 28 November 2017 / Revised: 2 January 2018 / Accepted: 6 January 2018 / Published: 9 January 2018
(This article belongs to the Special Issue Data Restoration and Denoising of Remote Sensing Data)
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Dispersive hyperspectral VNIR (visible and near-infrared) imagers using back-illuminated CCDs will suffer from interference fringes in near-infrared bands, which can cause a sensitivity modulation as high as 40% or more when the spectral resolution gets higher than 5 nm. In addition to the interference fringes that will change with time, there is fixed-pattern non-uniformity between pixels in the spatial dimension due to the small-scale roughness of the imager’s entrance slit, creating a much more complicated problem. A two-step method to remove fringes for dispersive hyperspectral VNIR imagers is proposed and evaluated. It first uses a ridge regression model to suppress the spectral fringes, and then computes spatial correction coefficients from the object data to correct the spatial fringes. In order to evaluate its effectiveness, the method was used to remove fringes for both the calibration data and object data collected from two VNIR grating-based hyperspectral imagers. Results show that the proposed method can preserve the original spectral shape, improve the image quality, and reduce the fringe amplitude in the 700–1000 nm region from about ±23% (10.7% RMSE) to about ±4% (1.9% RMSE). This method is particularly useful for spectra taken through a slit with a grating and shows flexible adaptability to object data, which suffer from time-varying interference fringes. View Full-Text
Keywords: hyperspectral; VNIR; interference fringes; ridge regression hyperspectral; VNIR; interference fringes; ridge regression

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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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Hu, B.; Sun, D.; Liu, Y. A Novel Method to Remove Fringes for Dispersive Hyperspectral VNIR Imagers Using Back-Illuminated CCDs. Remote Sens. 2018, 10, 79.

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