Dr. Zhenping Li Profile

Dr. Zhenping Li

Senior System Engineer at ASRC Federal

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Publications (6)

SPIE Journal Paper | 2 May 2023

Optimized image registration algorithm at subpixel level for Geostationary Operational Environmental Satellite-R Advanced Baseline Imager navigation and registration performance assessment

Zhenping Li

JARS, Vol. 17, Issue 02, 026504, (May 2023) https://doi.org/10.1117/12.10.1117/1.JRS.17.026504

KEYWORDS: Image registration, Landsat, Image quality, Correlation function, Mathematical optimization, Histograms, Image enhancement, Satellites, Satellite imaging, Image processing

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SPIE Journal Paper | 6 November 2014 Open Access

Geostationary Operational Environmental Satellite Imager infrared channel-to-channel co-registration characterization algorithm and its implementation in the ground system

Zhenping Li, Michael Grotenhuis, Xiangqian Wu, Timothy Schmit, Christopher Schmidt, Anthony Schreiner, James Nelson, Fangfang Yu, Hyre Bysal

JARS, Vol. 8, Issue 01, 083530, (November 2014) https://doi.org/10.1117/12.10.1117/1.JRS.8.083530

KEYWORDS: Infrared imaging, Imaging systems, Satellites, Satellite imaging, Earth observing sensors, Infrared radiation, Environmental sensing, Clouds, Infrared sensors, Fiber optic gyroscopes

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Channel-to-channel co-registration is an important performance metric for the Geostationary Operational Environmental Satellite (GOES) Imager, and large co-registration errors can have a significant impact on the reliability of derived products that rely on combinations of multiple infrared (IR) channels. Affected products include the cloud mask, fog and fire detection. This is especially the case for GOES-13, in which the co-registration error between channels 2 (3.9 μm) and 4 (10.7 μm) can be as large as 1 pixel (or ∼4 km) in the east-west direction. The GOES Imager IR channel-to-channel co-registration characterization (GII4C) algorithm is presented, which allows a systematic calculation of the co-registration error between GOES IR channel image pairs. The procedure for determining the co-registration error as a function of time is presented. The algorithm characterizes the co-registration error between corresponding images from two channels by spatially transforming one image using the fast Fourier transformation resampling algorithm and determining the distance of the transformation that yields the maximum correlation in brightness temperature. The GII4C algorithm is an area-based approach which does not depend on a fixed set of control points that may be impacted by the presence of clouds. In fact, clouds are a feature that enhances the correlations. The results presented show very large correlations over the majority of Earth-viewing pixels, with stable algorithm results. Verification of the algorithm output is discussed, and a global spatial-spectral gradient asymmetry parameter is defined. The results show that the spatial-spectral gradient asymmetry is strongly correlated to the co-registration error and can be an effective global metric for the quality of the channel-to-channel co-registration characterization algorithm. Implementation of the algorithm in the GOES ground system is presented. This includes an offline component to determine the time dependence of the co-registration errors and a real-time component to correct the co-registration errors based on the inputs from the offline component.

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SPIE Journal Paper | 29 January 2014 Open Access

Fast Fourier transformation resampling algorithm and its application in satellite image processing

Zhenping Li

JARS, Vol. 8, Issue 01, 083683, (January 2014) https://doi.org/10.1117/12.10.1117/1.JRS.8.083683

KEYWORDS: Satellites, Satellite imaging, Earth observing sensors, Image processing, Infrared imaging, Phase shifts, Imaging systems, Data modeling, Infrared radiation, Digital image processing

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Proceedings Article | 25 October 2012 Paper

Recent advances in calibration of the GOES Imager visible channel at NOAA

Charles Dean, I-Lok Chang, Zhenping Li, Michael Weinreb, Xiangqian Wu, Fangfang Yu

Proceedings Volume 8510, 85100M (2012) https://doi.org/10.1117/12.929036

KEYWORDS: Calibration, Stars, Imaging systems, Satellites, MODIS, Time metrology, Signal attenuation, Satellite imaging, Modulation, Visible radiation

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Proceedings Article | 15 October 2012 Paper

Refined algorithms for star-based monitoring of GOES Imager visible-channel responsivities

I-Lok Chang, Charles Dean, Zhenping Li, Michael Weinreb, Xiangqian Wu, P. Swamy

Proceedings Volume 8510, 85100R (2012) https://doi.org/10.1117/12.928892

KEYWORDS: Stars, Sensors, Imaging systems, Satellites, Signal detection, Calibration, Signal processing, Satellite imaging, Surface plasmons, Reliability

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Proceedings Article | 21 August 2008 Paper

Using raw star signals in the monitoring of GOES imager visible-channel responsivities

I-Lok Chang, Charles Dean, Michael Weinreb, Xiangqian Wu, Dejiang Han, Kenneth Mitchell, Zhenping Li, Gordana Sindic-Rancic, Fanfang Yu

Proceedings Volume 7081, 70810G (2008) https://doi.org/10.1117/12.795751

KEYWORDS: Stars, Sensors, Imaging systems, Signal detection, Satellites, Signal to noise ratio, Calibration, Navigation systems, Roads, Satellite imaging

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Showing 5 of 6 publications

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