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%% This BibTeX bibliography file was created using BibDesk.
%% http://bibdesk.sourceforge.net/
%% Created for Jonny Dyer at 2017-04-19 17:16:36 -0700
%% Saved with string encoding Unicode (UTF-8)
@techreport{niirs,
Author = {L. A. Maver and C. D. Erdman and K. Riehl},
Date-Added = {2017-04-19 23:57:09 +0000},
Date-Modified = {2017-04-20 00:16:34 +0000},
Month = {April},
Title = {National Image Interpretability Rating Scales},
note = "Available online [\url{https://fas.org/irp/imint/niirs.htm}]",
Year = {2017}}
@inproceedings{giqe5,
Author = {Doug Griffith},
Booktitle = {JACIE Conference},
Date-Added = {2017-04-19 22:37:33 +0000},
Date-Modified = {2017-04-19 22:39:55 +0000},
Title = "General Image Quality Equation ({GIQE})",
Year = {2012},
note = "Available online [\url{https://calval.cr.usgs.gov/wordpress/wp-content/uploads/Griffith_Doug_JACIEGIQERev3cor2sjs6with-Caveat.pdf}]"
}
@inproceedings{meinel,
Author = {Aden B. Meinel},
Year = {1978},
Booktitle = {ESO Conference Proceedings},
Title = {An Overview of the Technological Possibilities of Future Telescopes},
Editor = {F. Pacini, W. Richter, R. N. Wilson},
Pages = {13-26}
}
@techreport{jerram,
Author = {Paul Jerram and David Morris},
Date-Added = {2017-03-14 22:26:54 +0000},
Date-Modified = {2017-03-14 22:28:29 +0000},
Institution = {e2V},
Title = {Recent Sensor Designs for Earth Observation},
note = "Available online [\url{http://www.e2v.com/content/uploads/2014/02/EO-Image-sensors-DJB.pdf}]",
Year = {2014},
}
@proceeding{tdi_smear,
author = { Walid A. Wahballah,Taher M. Bazan,Fawzy El-Tohamy,Mahmoud Fathy},
title = {Analysis of smear in high-resolution remote sensing satellites},
journal = {Proc.SPIE},
volume = {10000},
number = {},
pages = {10000 - 10000 - 11},
year = {2016},
doi = {10.1117/12.2241634},
URL = {https://doi.org/10.1117/12.2241634},
note = "[doi:10.1117/12.2241634]"
}
@book{fiete,
Address = {PO Box 10; Bellingham, Washington 98277-0010},
Author = {Robert E. Fiete},
Date-Added = {2015-11-15 18:30:58 +0000},
Date-Modified = {2015-11-15 18:33:04 +0000},
Publisher = {SPIE Press},
Title = {Modeling the Image Chain of Digital Cameras},
Volume = {TT92},
Year = {2010},
note = "[doi:10.1117/3.868276]"
}
@conference{pittelkau,
Author = {Mark E. Pittelkau and William G. McKinley},
Booktitle = {AIAA/AAS Astrodynamics Specialist Conference},
Date-Added = {2015-11-15 18:15:30 +0000},
Date-Modified = {2015-11-15 18:18:52 +0000},
Month = {August},
Number = {AIAA 2012-4009},
Organization = {American Institude of Aeronautics and Astronautics},
Publisher = {AIAA},
Title = {Pointing Error Metrics: Displacement, Smear, Jitter and Smitter},
Year = {2012},
note = "[doi:10.2514/6.2012-4869]"
}
@article{fiete_blur,
Abstract = {Space-based high-resolution scanning array imaging systems have the potential to introduce large amounts of image smear. When designing these systems, it is useful to understand how smear will degrade image quality. A brief description of the causes of smear and a simple mathematical model are presented. A series of image simulations (for a system in which λFN/p=1.0, where λ is the mean wavelength for a panchromatic system, FN is the system f number, and p is the pixel pitch of the detectors) are performed in which along scan smear (ranging from 1.0 to 8.0 pixels) is introduced. Using the National Imagery Interpretability Rating Scale (NIIRS), expert observers rated ΔNIIRS difference in image quality between the images with simulated smear and the original ``unsmeared'' image. The functional relationship between smear error and image quality (in units of ΔNIIRS) is determined. {\copyright} 1999 Society of Photo-Optical Instrumentation Engineers.},
Author = {Smith, Steven L. and Mooney, James and Tantalo, Theodore A. and Fiete, Robert D.},
Doi = {10.1117/1.602054},
Isbn = {0091-3286},
Journal = {Optical Engineering},
Number = {5},
Pages = {821-826},
Title = {Understanding image quality losses due to smear in high-resolution remote sensing imaging systems},
Url = {http://dx.doi.org/10.1117/1.602054},
Volume = {38},
Year = {1999},
note = "[doi:10.1117/1.602054]"
}
@article{fiete_Q_IQ,
Abstract = {Commercial remote sensing systems generally employ a linear detector array for imaging the ground scene. Strategies for increasing the ground sampling along one direction of the array can be employed to improve the image quality. Image simulations were generated to quantify the image quality improvement, in terms of the National Image Interpretability Scale (NIIRS), as the sampling is increased in the along-scan (A/S) direction of the array. The simulations modeled a remote sensing system with λFN/p=1 (where FN is the system f-number and p is the detector sampling pitch) and show that an image quality improvement of approximately 0.35 NIIRS can be achieved if the sampling rate is increased in the A/S direction by 2×. {\copyright} 1999 Society of Photo-Optical Instrumentation Engineers.},
Author = {Fiete, Robert D. and Tantalo, Theodore A.},
Doi = {10.1117/1.602053},
Isbn = {0091-3286},
Journal = {Optical Engineering},
Number = {5},
Pages = {815-820},
Title = {Image quality of increased along-scan sampling for remote sensing systems},
Url = {http://dx.doi.org/10.1117/1.602053},
Volume = {38},
Year = {1999},
note = "[doi:10.1117/1.602053]"}
@article{fiete_snr_IQ,
Abstract = {Different definitions of the signal-to-noise ratio (SNR) are being used as metrics to describe the image quality of remote sensing systems. It is usually not clear which SNR definition is being used and what the image quality of the system is when an SNR value is quoted. This paper looks at several SNR metrics used in the remote sensing community. Image simulations of the Kodak Space Remote Sensing Camera, Model 1000, were produced at different signal levels to give insight into the image quality that corresponds with the different SNR metric values. The change in image quality of each simulation at different signal levels is also quantified using the National Imagery Interpretability Rating Scale (NIIRS) and related to the SNR metrics to better understand the relationship between the metric and image interpretability. An analysis shows that the loss in image interpretability, measured as ΔNIIRS, can be modeled as a linear relationship with the noise-equivalent change in reflection (NEΔρ). This relationship is used to predict the values that the various SNR metrics must exceed to prevent a loss in the interpretability of the image from the noise. {\copyright} 2001 Society of Photo-Optical Instrumentation Engineers.},
Author = {Fiete, Robert D. and Tantalo, Theodore},
Doi = {10.1117/1.1355251},
Isbn = {0091-3286},
Journal = {Optical Engineering},
Number = {4},
Pages = {574-585},
Title = {Comparison of SNR image quality metrics for remote sensing systems},
Url = {http://dx.doi.org/10.1117/1.1355251},
Volume = {40},
Year = {2001},
note = "[doi:10.1117/1.1355251]"}
@article{fiete_q,
Abstract = {The ratio of the sampling frequency to the optical bandpass limit of an incoherent diffraction-limited optical system is a fundamental design parameter for digital imaging systems. This ratio is denoted by $\lambda$FN/p, where $\lambda$ is the mean wavelength, FN is the system f/number, and p is the detector sampling pitch. The value of $\lambda$FN/p for a remote sensing system can have a profound impact on the image quality and the utility of the acquired images. The interaction between $\lambda$FN/p and image quality is sensitive to the system design parameters such as modulation transfer function (MTF), signal-to-noise ratio (SNR), and ground sampled distance (GSD). Image simulations and analysis are presented that illustrate the changes in image quality as a function of $\lambda$FN/p. System design trades that may influence the determination of the optimal $\lambda$FN/p for a remote sensing system are also discussed. {\copyright} 1999 Society of Photo-Optical Instrumentation Engineers.},
Author = {Fiete, Robert D.},
Doi = {10.1117/1.602169},
Isbn = {0091-3286},
Journal = {Optical Engineering},
Number = {7},
Pages = {1229-1240},
Title = {Image quality and $\lambda$FN/p for remote sensing systems},
Url = {http://dx.doi.org/10.1117/1.602169},
Volume = {38},
Year = {1999},
note = "[doi:10.1117/1.602169]"}
@techreport{auelmann_iq,
Abstract = {},
Author = {Auelmann, Richard R.},
Doi = {},
Isbn = {},
Title = {Image Quality Metrics},
note = "Available online [\url{http://www.techarchive.org/wp-content/themes/boilerplate/largerdocs/Image%20Quality%20Metrics.pdf}]",
Year = {2012},
}
@techreport{isscc2016,
Abstract = {},
Author = {},
Title = {{ISSCC} Trends 2016},
note = "Available online [\url{http://isscc.org/doc/2016/ISSCC2016_TechTrends.pdf}]",
Year = {2016},
}
@article{shaw,
Abstract = {Spectral imaging for remote sensing of terrestrial features and objects arose as an alternative to high-spatial-resolution, large-aperture satellite imaging systems. Early applications of spectral imaging were oriented toward ground-cover classification, mineral exploration, and agricultural assessment, employing a small number of carefully chosen spectral bands spread across the visible and infrared regions of the electromagnetic spectrum. Improved versions of these early multispectral imaging sensors continue in use today. A new class of sensor, the hyperspectral imager, has also emerged, employing hundreds of contiguous bands to detect and identify a variety of natural and man-made materials. This overview article introduces the fundamental elements of spectral imaging and discusses the historical evolution of both the sensors and the target detection and classification applications.},
Author = {Shaw, Gary A. and Burke, Hsiao-hua K.},
Journal = {Lincoln Laboratory Journal},
Number = {1},
Title={Spectral Imaging for Remote Sensing},
Volume = {14},
Pages = {3-28},
Year = {2003},
Url = {http://llwww.ll.mit.edu/publications/journal/pdf/vol14_no1/14_1remotesensing.pdf},
note = "[doi:10.1.1.69.1178]"
}
@patent{patent:jonny,
author = {Jonathan Dyer},
title = {Capturing images using controlled vibration},
language = {English},
nationality = {United States},
type = {},
number = {9509894},
day = {29},
dayfiled = {},
month = {11},
monthfiled = {},
year = {2016},
yearfiled = {},
note = "\href{https://www.google.com/patents/US9509894}{US Patent 9,509,894}",
url = {https://www.google.com/patents/US9509894},
}
@patent{patent:dirk,
author = {M Dirk Robinson and Jonathan Dyer and Joshua Levine and Brendan Hermalyn and Ronny Votel and Matt William Messana},
title = {Controlling a Line of Sight Angle of an Imaging Platform},
language = {English},
nationality = {United States},
type = {Patent Application},
number = {15,230,785},
day = {8},
dayfiled = {},
month = {8},
monthfiled = {},
year = {2016},
yearfiled = {},
note = "\href{https://www.google.com/patents/US20170041548}{US Patent 15,230,785}",
url = {https://www.google.com/patents/US20170041548},
}
@article{careful_cots,
Address = {1801 Alexander Bell Drive, Reston, VA 20191-4344},
Author = {Doug Sinclair and Jonathan Dyer},
Date-Added = {2014-10-29 15:50:07 +0000},
Date-Modified = {2014-10-29 15:55:58 +0000},
Journal = {Conference on Small Sateilltes},
Month = {August},
Number = {SSC13-IV-3},
Title = {Radiation Effects and {COTS} Parts in SmallSats},
Year = {2013}
note = "Available online [\url{https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=2934&context=smallsat}]"
}
@book{bearden,
Address = {401 Coral Circle, El Segundo, CA 90245-4622 USA},
Author = {David Bearden and Richard Boudreault and James R. Wertz},
Chapter = {Cost Modeling},
Date-Added = {2014-10-27 04:42:26 +0000},
Date-Modified = {2014-10-27 16:45:12 +0000},
Editor = {James R. Wertz and Wiley J. Larson},
Pages = {253-284},
Publisher = {Microcosm Press},
Title = {Reducing Space Mission Cost},
Year = {1996}
}
@article{space_bandwidth,
Author = {Adolf W. Lohmann and Rainer G. Dorsch and David Mendlovic and Zeev Zalevsky and Carlos Ferreira},
Date-Added = {2014-10-26 19:16:58 +0000},
Date-Modified = {2014-10-26 19:20:29 +0000},
Journal = {Journal of Optical Society of America},
Month = {March},
Number = {3},
Pages = {470-473},
Title = {Space-bandwidth product of optical signals and systems},
Volume = {13},
Year = {1996},
}
@article{morfitt2015landsat,
title="Landsat-8 Operational Land Imager ({OLI}) radiometric performance on-orbit",
author={Morfitt, Ron and Barsi, Julia and Levy, Raviv and Markham, Brian and Micijevic, Esad and Ong, Lawrence and Scaramuzza, Pat and Vanderwerff, Kelly},
journal={Remote Sensing},
volume={7},
number={2},
pages={2208--2237},
year={2015},
publisher={Multidisciplinary Digital Publishing Institute}
},
@article{rushton,
author={J. Rushton and A. Holland and K. Stefanov and F. Mayer},
title={Characterisation of a CMOS charge transfer device for TDI imaging},
journal={Journal of Instrumentation},
volume={10},
number={03},
pages={C03027},
url={http://stacks.iop.org/1748-0221/10/i=03/a=C03027},
year={2015},
abstract={The performance of a prototype true charge transfer imaging sensor in CMOS is investigated. The finished device is destined for use in TDI applications, especially Earth-observation, and to this end radiation tolerance must be investigated. Before this, complete characterisation is required. This work starts by looking at charge transfer inefficiency and then investigates responsivity using mean-variance techniques.
},
note = "[doi:10.1088/1748-0221/10/03/C03027]"
}