Surveillance and Reconnaissance Imaging Systems

by Jon C Leachtenauer, Ronald G Driggers

Overview

Here's an up-to-date, comprehensive review of surveillance and reconnaissance (S&R) imaging system modeling and performance prediction. This new, one-of-a-kind resource helps you predict the information potential of new surveillance system designs, compare and select from alternative measures of information extraction, relate the performance of tactical acquisition sensors and surveillance sensors, and understand the relative importance of each element of the image chain on S&R system performance. It provides you with system descriptions and characteristics, S&R modeling history, and performance modeling details.

With an emphasis on validated prediction of human observer performance, this unique book addresses the specific design and analysis techniques used with today's S&R imaging systems. You find in-depth discussions on everything from the conceptual performance prediction model, linear shift invariant systems, and measurement variables used for S&R information extraction... to predictor variables, target and environmental considerations, CRT and flat panel display selection, and models for image processing. Conversion methods between alternative modeling approaches are examined to help you perform system comparisons. Supported with 120 illustrations and 150 equations.

Product Details

ISBN-13:	9781580531320
Publisher:	Artech House, Incorporated
Publication date:	03/31/2001
Series:	Artech House Optoelectronics Library
Pages:	424
Product dimensions:	6.50(w) x 9.30(h) x 1.30(d)

About the Author

Jon C. Leachtenauer formed his own consulting agency, J/M Leachtenauer Associates, Inc, and is currently a consultant to the National Imagery and Mapping Agency. He is the author of over 150 technical reports, as well as numerous published papers covering all aspects of the image exploitation process. Mr. Leachtenauer holds an A.B. and M.S. in Geology from Syracuse University.

Ronald G. Driggers is a senior engineer with the U.S. Army Night Vision and Electronic Sensors Directorate and is the U.S. representative to the NATO panel on advanced thermal imager characterization. Dr. Driggers is the author of two other books on infrared and electro-optic systems and has published over 30 refereed journal papers. He holds a Ph.D. in electrical engineering from the University of Memphis.

Table of Contents

	Preface	xv
	Acknowledgments	xvii
1	Introduction	1
1.1	Modeling Applications	2
1.2	Conceptual S&R Model	3
1.3	Performance Prediction Approaches	8
1.3.1	Physical Image Quality	8
1.3.2	Physical Models and Simulations	9
1.3.3	Information Theory-Based Models	10
1.3.4	Difference Models and Metrics	11
1.4	Summary	12
	References	12
2	Surveillance and Reconnaissance Imaging Systems	13
2.1	Introduction	13
2.2	Imaging with IR and EO Sensors	16
2.2.1	Infrared Sensors	16
2.2.2	Electro-Optical Sensors	19
2.3	Image Formation	20
2.3.1	Line Scanners	20
2.3.2	Staring Array Sensors	22
2.3.3	Television Sensors	23
2.3.4	Analog versus Digital Signals	24
2.4	Imaging System Parameters	25
2.4.1	Sensitivity and Resolution	25
2.4.2	Field of View	26
2.4.3	Field of Regard	27
2.4.4	Diffraction	27
2.4.5	Detector Angular Subtense and Instantaneous Field of View	29
2.4.6	Ground Sample Distance	30
2.4.7	Point Spread Function	32
2.5	Synthetic Aperture Radar	33
2.6	Choice of Imaging Sensors	37
2.7	Examples of Surveillance and Reconnaissance Sensors	39
2.7.1	Predator	39
2.7.2	Global Hawk	41
2.7.3	Landsat 7	42
2.7.4	RADARSAT	45
2.7.5	IKONOS	47
2.7.6	Russian Satellite Imagery	47
2.7.7	Other Satellite Systems	49
	References	50
3	Historical Review	53
3.1	Pre-1950	53
3.2	1950-1970	57
3.3	1970 to Present	64
3.4	Summary	68
	References	69
4	Linear Shift Invariant Imaging Systems	75
4.1	Linearity and Shift Invariance	75
4.2	The Impulse Function	77
4.3	The Fourier Series and Fourier Transform	79
4.3.1	Fourier Series	79
4.3.2	Fourier Transform	80
4.3.3	Fourier Transform Properties	81
4.3.4	Fourier Transform Pairs	82
4.4	LSI Imaging System	83
4.5	Imaging in the Space and Frequency Domains	85
4.6	Imaging with Components	85
4.6.1	Optics	89
4.6.2	Detectors	90
4.6.3	Electronics	94
4.6.4	Displays	99
4.6.5	Human Vision	101
4.7	Simplifying LSI Imager Analysis to One Dimension	103
4.8	Sampled Imaging Systems	108
4.9	SAR Impulse Response and Transfer Function	110
4.10	Summary	111
	References	111
5	Information Extraction Measures	115
5.1	Direct Performance Measures	116
5.1.1	Probability of Task Performance	116
5.1.2	Completeness and Accuracy	119
5.1.3	Statistical Properties of Direct Measures	120
5.2	Theory of Signal Detection	124
5.3	Range/Time Measures	128
5.4	Performance Estimate Measures	129
5.4.1	National Imagery Interpretability Rating Scale	132
5.4.2	Task Satisfaction Confidence Ratings	145
5.4.3	Relative Quality Scales	148
5.5	Information and Difference Metrics	152
5.6	Summary	156
	References	156
6	Information Extraction Performance Predictors	159
6.1	Scale, Resolution, and Sharpness	160
6.1.1	Scale	160
6.1.2	Photographic Resolution	162
6.1.3	Video Resolution (Analog)	167
6.1.4	Electro-optical Systems	170
6.1.5	SAR Resolution	174
6.2	Contrast and Noise	177
6.2.1	Photographic Measures	177
6.2.2	Electro-optical Measures	181
6.2.3	SAR Measures	182
6.3	Artifacts	185
6.4	Summary Measures	188
6.4.1	Regression Models	188
6.4.2	MTF	188
6.4.3	MTF Measures	191
6.4.4	SNR Measures	194
6.4.5	Physical Difference Metrics	196
6.5	Summary	197
	References	198
7	Target and Environmental Considerations	203
7.1	Target Effects	203
7.2	Deception and Denial	216
7.3	Atmospheric Effects	220
7.4	Summary	222
	References	223
8	Image Processing Considerations	225
8.1	Bandwidth Compression	225
8.1.1	Single Image Monochrome Compression	228
8.1.2	Multichannel Image Compression	233
8.1.3	Motion Imagery Compression	236
8.2	Enhancement Processing	241
8.2.1	Spatial Filtering	242
8.2.2	Pixel Intensity Transforms	245
8.2.3	Image Fusion	249
8.3	Summary	250
	References	251
	Selected Bibliography	252
9	Display and Observer Considerations	255
9.1	Displays	255
9.1.1	Briggs Targets	256
9.1.2	CRT Displays	258
9.1.3	Flat Panel Displays	271
9.1.4	Display Environment	273
9.2	Observer Characteristics	278
9.2.1	Observer Selection	278
9.2.2	Observer Variability	282
9.3	Observer Models	284
9.4	Summary	293
	References	294
10	Performance Prediction Models	299
10.1	Parameter-Based Models	300
10.1.1	General Image Quality Equation	301
10.1.2	Target Acquisition Sensor Performance Modeling	312
10.1.3	Physique	326
10.1.4	Radar Threshold Quality Factor	328
10.1.5	Other SAR Models	329
10.2	Image-Based Models	330
10.2.1	Image Quality Model	331
10.2.2	Sarnoff JND Model	334
10.2.3	Other Image-Based Models	339
10.3	Summary	344
	References	344
11	Sensor Performance Conversions	349
11.1	Johnson Criteria and NIIRS	351
11.2	Conversions with Models	352
11.3	Comparing Sensor Performance Conversions	356
11.4	Performance Conversion as a Function of Target Size	360
11.5	Summary	360
	References	362
12	Conclusions and Future Directions	365
12.1	Spectral Domain	366
12.2	Temporal Effects	368
12.3	Search	369
12.4	SAR	371
12.5	Summary	374
	References	376
	List of Acronyms	379
	About the Authors	385
	Index	387

Editorial Reviews

Leachtenauer, a human factors professional and consultant to the National Imagery and Mapping Agency, and Driggers, an electro-optical specialist now with the US Army, explain to design engineers, system analysts, and image scientists how to model imaging systems and predict their performance based on design attributes and measurable operating parameters. They consider the history of imaging systems, linear shift invariant systems, information extraction measures, information extraction performance predictors, target and environmental considerations, imaging processing considerations, display and observer considerations, performance prediction models, sensor performance conversions, and future directions. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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