Image Chain Simulation for Earth Observation Satellites

We present a general-purpose end-to-end image chain simulation (ICS) that enables to assess the image quality of a satellite imager for Earth observations. The image chain consists of four main components: radiometry, atmosphere, optics, and detector. In particular, ICS first computes the input radiance from the reflectance values of a high-resolution input, and then calculates the image radiance by using the optical transfer function (OTF) of the overall system. This OTF contains all the distortion effects due to atmosphere, optics, and detector. Finally, the signal on the detector, including the noise term, is computed and converted to digital counts. To evaluate the overall image quality, metrics such as peak signal-to-noise ratio and minimum resolvable contrast are used. To illustrate the utility and versatility of the developed ICS, several analyses are also performed that demonstrate the system performance of a generic satellite imagery. Our development provides a unified framework for the ICS developers of spaceborne Earth-observing systems. Such a complete end-to-end ICS is crucial for the effective development of an Earth observation satellite, especially in the design and test phases.

[1]  J. Walkup,et al.  Statistical optics , 1986, IEEE Journal of Quantum Electronics.

[2]  S. Hook,et al.  The ASTER spectral library version 2.0 , 2009 .

[3]  Ralf Reulke,et al.  Simulation of APEX data: the SENSOR approach , 1999, Optics & Photonics.

[4]  Robert A. Schowengerdt,et al.  IKONOS Spatial Resolution and Image Interpretability Characterization , 2003 .

[5]  FlOg LeI'tl.  Atmospheric influence on image quality of airborne photographs , .

[6]  John R. Schott,et al.  Image quality analysis of a spectra-radiometric sparse-aperture model , 2004, SPIE Defense + Commercial Sensing.

[7]  John R. Schott,et al.  Remote Sensing: The Image Chain Approach , 1996 .

[8]  Adriaan van den Bos,et al.  Resolution: a survey , 1997 .

[9]  Hermann Kaufmann,et al.  EeteS: An end-to-end image simulation tool applied to THE EnMAP hyperspectral mission , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[10]  Robert E. Introne,et al.  Enhanced Spectral Modeling of Sparse Aperture Imaging Systems , 2004 .

[11]  Carine Babusiaux.  The Gaia instrument and basic image simulator , 2005 .

[12]  Robert D. Fiete,et al.  Image quality of sparse-aperture designs for remote sensing , 2002 .

[13]  A. Berk.  MODTRAN : A moderate resolution model for LOWTRAN7 , 1989 .

[14]  Daniel Wintz,et al.  PICASSO: an end-to-end image simulation tool for space and airborne imaging systems II. Extension to the thermal infrared: equations and methods , 2011, Optical Engineering + Applications.

[15]  Glenn D. Boreman,et al.  Modulation Transfer Function in Optical and Electro-Optical Systems , 2001 .

[16]  Christopher J. Florio,et al.  PICASSO: an end-to-end image simulation tool for space and airborne imaging systems , 2010 .

[17]  David R. Filbee,et al.  Modeling of high-fidelity synthetic imagery for defense applications , 2002, SPIE Defense + Commercial Sensing.

[18]  R.E. Introne,et al.  Comparison of monochromatic and polychromatic modeling of sparse-aperture image quality , 2005, 2005 IEEE Aerospace Conference.

[19]  H. K. Ramapriyan.  Satellite Imagery in Earth Science Applications , 2002 .

[20]  Robert D. Fiete,et al.  Modeling the Imaging Chain of Digital Cameras , 2010 .

[21]  Felix Stoehr,et al.  WFC3 Support in Tiny Tim , 2008 .

[22]  Marilyn A. Gilmore,et al.  CAMEO-SIM: a physics-based broadband scene simulation tool for assessment of camouflage, concealment, and deception methodologies , 2001 .

[23]  John E. Krist,et al.  20 years of Hubble Space Telescope optical modeling using Tiny Tim , 2011 .

[24]  R. Smith,et al.  Linear Systems, Fourier Transforms and Optics , 1979 .

[25]  D Sadot,et al.  Effects of absorption on image quality through a particulate medium. , 1994, Applied optics.

[26]  Luciano Alparone,et al.  End-to-End Image Simulator for Optical Imaging Systems: Equations and Simulation Examples , 2013 .

[27]  Peter B. Catrysse,et al.  A simulation tool for evaluating digital camera image quality , 2003, IS&T/SPIE Electronic Imaging.

[28]  R. Richter,et al.  Sensor: a tool for the simulation of hyperspectral remote sensing systems , 2001 .

[29]  Colin A. Stroud,et al.  CAMEO-SIM: a broadband scene generation system that is fit for purpose , 1999, Defense, Security, and Sensing.

[30]  Xing-Fei He,et al.  Time Delay Integration Speeds Up Imaging , 2012 .

[31]  Luis Guanter,et al.  S2eteS: An End-to-End Modeling Tool for the Simulation of Sentinel-2 Image Products , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Edward L. O’Neill.  Transfer Function for an Annular Aperture , 1956 .

[33]  Lili Jiang,et al.  Image resolution analysis of atmospheric turbulence on the high-resolution space optical systems , 2015, International Conference on Optical Instruments and Technology.

[34]  Craig Loomis,et al.  ERIS: the exoplanet high-resolution image simulator for CHARIS , 2014, Astronomical Telescopes and Instrumentation.