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Introductory Digital Image Processing,9780131453616
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Introductory Digital Image Processing

by
Edition:
3rd
ISBN13:

9780131453616

ISBN10:
0131453610
Format:
Hardcover
Pub. Date:
4/30/2004
Publisher(s):
Prentice Hall

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Summary

For junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology.This revision of Introductory Digital Image Processing: A Remote Sensing Perspective continues to focus on digital image processing of aircraft- and satellite-derived, remotely sensed data for Earth resource management applications. Extensively illustrated, it explains how to extract biophysical information from remote sensor data for almost all multidisciplinary land-based environmental projects. Part of the Prentice Hall Series Geographic Information Science.

Table of Contents

Preface xiii
Acknowledgments xvi
Remote Sensing and Digital Image Processing
1(34)
In Situ Data Collection
1(2)
In Situ Data-Collection Error
2(1)
Remote Sensing Data Collection
3(3)
Observations about Remote Sensing
4(1)
Remote Sensing Advantages and Limitations
5(1)
The Remote Sensing Process
6(22)
Statement of the Problem
7(2)
Identification of In Situ and Remote Sensing Data Requirement
9(3)
Remote Sensing Data Collection
12(12)
Remote Sensing Data Analysis
24(4)
Information Presentation
28(1)
Earth Resource Analysis Perspective
28(1)
Book Organization
28(2)
References
30(5)
Remote Sensing Data Collection
35(72)
Analog (Hard-Copy) Image Digitization
35(9)
Digital Image Terminology
35(1)
Microdensitometer Digitization
36(2)
Video Digitization
38(1)
Linear and Area Array Charge-Coupled-Device Digitization
39(2)
Digitized National Aerial Photography Program Data
41(1)
Digitization Considerations
41(3)
Digital Remote Sensor Data Collection
44(3)
Multispectral Imaging Using Discrete Detectors and Scanning Mirrors
47(27)
Earth Resource Technology Satellites and Landsat Sensor Systems
47(15)
NOAA Multispectral Scanner Sensors
62(6)
ORBIMAGE, Inc., and NASA Sea-viewing Wide Field-of-view Sensor
68(3)
Aircraft Multispectral Scanners
71(3)
Multispectral Imaging Using Linear Arrays
74(16)
SPOT Sensor Systems
74(8)
Indian Remote Sensing Systems
82(1)
Advanced Spaceborne Thermal Emission and Reflection Radiometer
83(2)
Multiangle Imaging Spectroradiometer
85(1)
Very-High-Resolution Linear Array Remote Sensing Systems
86(4)
Imaging Spectrometry Using Linear and Area Arrays
90(5)
Airborne Visible/Infrared Imaging Spectrometer
91(1)
Compact Airborne Spectrographic Imager 3
92(1)
Moderate Resolution Imaging Spectrometer
92(3)
Digital Frame Cameras
95(3)
Digital Frame Camera Data Collection
96(2)
Emerge, Inc., Digital Sensor System
98(1)
Satellite Photographic Systems
98(3)
Russian SPIN-2 TK-350 and KVR-1000 Cameras
98(3)
U.S. Space Shuttle Photography
101(1)
Digital Image Data Formats
101(2)
Band Interleaved by Pixel Format
102(1)
Band Interleaved by Line Format
102(1)
Band Sequential Format
103(1)
Summary
103(1)
References
104(3)
Digital Image Processing Hardware and Software Considerations
107(20)
Digital Image Processing System Considerations
107(1)
Central Processing Units, Personal Computers, Workstations, and Mainframes
108(2)
Personal Computer
110(1)
Computer Workstations
110(1)
Mainframe Computers
110(1)
Read-Only Memory, Random Access Memory, Serial and Parallel Processing, and Arithmetic Coprocessor
110(3)
Read-Only Memory and Random Access Memory
113(1)
Serial and Parallel Image Processing
113(1)
Arithmetic Coprocessor
113(1)
Mode of Operation and Interface
113(2)
Mode of Operation
113(1)
Graphical User Interface
114(1)
Computer Operating System and Compiler(s)
115(2)
Operating System
117(1)
Compiler
117(1)
Storage and Archiving Considerations
117(1)
Rapid Access Mass Storage
117(1)
Archiving Considerations: Longevity
118(1)
Computer Display Spatial and Color Resolution
118(2)
Computer Screen Display Resolution
118(1)
Computer Screen Color Resolution
118(2)
Important Image Processing Functions
120(1)
Commercial and Public Digital Image Processing Systems
121(1)
Digital Image Processing and the National Spatial Data Infrastructure
121(2)
Sources of Digital Image Processing Systems
123(1)
References
124(3)
Image Quality Assessment and Statistical Evaluation
127(24)
Image Processing Mathematical Notation
127(1)
Sampling Theory
128(1)
The Histogram and Its Significance to Digital Image Processing
128(4)
Image Metadata
132(1)
Viewing Individual Pixel Brightness Values at Specific Locations or within a Geographic Area
132(3)
Cursor Evaluation of Individual Pixel Brightness Values
132(1)
Two- and Three-dimensional Evaluation of Pixel Brightness Values within a Geographic Area
133(2)
Univariate Descriptive Image Statistics
135(2)
Measure of Central Tendency in Remote Sensor Data
135(1)
Measures of Dispersion
135(2)
Measures of Distribution (Histogram) Asymmetry and Peak Sharpness
137(1)
Multivariate Image Statistics
137(4)
Covariance in Multiple Bands of Remote Sensor Data
138(1)
Correlation between Multiple Bands of Remotely Sensed Data
139(2)
Feature Space Plots
141(1)
Geostatistical Analysis
141(7)
Relationships among Geostatistical Analysis, Autocorrelation, and Kriging
141(2)
Calculating Average Semivariance
143(1)
Empirical Semivariagram
144(4)
References
148(3)
Initial Display Alternatives and Scientific Visualization
151(24)
Image Display Considerations
151(3)
Black-and-White Hard-copy Image Display
154(1)
Line Printer/Plotter Brightness Maps
154(1)
Laser or Ink-jet Printer Brightness Maps
154(1)
Temporary Video Image Display
154(10)
Black-and-White and Color Brightness Maps
154(1)
Bitmapped Graphics
154(3)
RGB Color Coordinate System
157(1)
Color Look-up Tables: 8-bit
158(1)
Color Look-up Tables: 24-bit
159(2)
Color Composites
161(3)
Merging Remotely Sensed Data
164(5)
Band Substitution
164(1)
Color Space Transformation and Substitution
164(4)
Principal Component Substitution
168(1)
Pixel-by-Pixel Addition of High-Frequency Information
169(1)
Smoothing Filter-based Intensity Modulation Image Fusion
169(1)
Distance, Area, and Shape Measurement
169(3)
Distance Measurement
169(2)
Area Measurement
171(1)
Shape Measurement
172(1)
References
172(3)
Electromagnetic Radiation Principles and Radiometric Correction
175(52)
Electromagnetic Energy Interactions
176(1)
Conduction, Convection, and Radiation
176(1)
Electromagnetic Radiation Models
176(9)
Wave Model of Electromagnetic Energy
176(5)
The Particle Model: Radiation from Atomic Structures
181(4)
Atmospheric Energy--Matter Interactions
185(6)
Refraction
185(1)
Scattering
186(2)
Absorption
188(2)
Reflectance
190(1)
Terrain Energy--Matter Interactions
191(3)
Hemispherical Reflectance, Absorptance, and Transmittance
191(1)
Radiant Flux Density
192(2)
Energy--Matter Interactions in the Atmosphere Once Again
194(1)
Energy--Matter Interactions at the Sensor System
194(1)
Correcting Remote Sensing System Detector Error
194(4)
Random Bad Pixels (Shot Noise)
195(1)
Line or Column Drop-outs
195(1)
Partial Line or Column Drop-outs
195(2)
Line-start Problems
197(1)
N-line Striping
198(1)
Remote Sensing Atmospheric Correction
198(22)
Unnecessary Atmospheric Correction
198(4)
Necessary Atmospheric Correction
202(1)
Types of Atmospheric Correction
202(1)
Absolution Radiometric Correction of Atmospheric Attenuation
203(10)
Relative Radiometric Correction of Atmospheric Attenuation
213(7)
Correcting for Slope and Aspect Effects
220(2)
The Cosine Correction
221(1)
The Minnaert Correction
221(1)
A Statistical--Empirical Correction
222(1)
The C Correction
222(1)
References
222(5)
Geometric Correction
227(28)
Internal and External Geometric Error
227(7)
Internal Geometric Error
227(5)
External Geometric Error
232(2)
Types of Geometric Correction
234(16)
Image-to-Map Rectification
235(1)
Image-to-Image Registration
236(1)
Hybrid Approach to Image Rectification/Registration
236(1)
Image-to-Map Geometric Rectification Logic
236(8)
Example of Image-to-Map Rectification
244(6)
Mosaicking
250(2)
Mosaicking Rectified Images
250(2)
References
252(3)
Image Enhancement
255(82)
Image Reduction and Magnification
255(2)
Image Reduction
255(1)
Image Magnification
256(1)
Transects (Spatial Profiles)
257(5)
Spectral Profiles
262(4)
Contrast Enhancement
266(8)
Linear Contrast Enhancement
266(6)
Nonlinear Contrast Enhancement
272(2)
Band Ratioing
274(2)
Spatial Filtering
276(20)
Spatial Convolution Filtering
276(11)
The Fourier Transform
287(9)
Principal Components Analysis
296(5)
Vegetation Transformations (Indices)
301(21)
Dominant Factors Controlling Leaf Reflectance
301(9)
Vegetation Indices
310(12)
Texture Transformations
322(7)
First-order Statistics in the Spatial Domain
322(2)
Second-order Statistics in the Spatial Domain
324(2)
Texture Units as Elements of a Texture Spectrum
326(1)
Fractal Dimension as a Measure of Spatial Complexity or Texture
327(2)
Texture Statistics Based on the Semi-variogram
329(1)
References
329(8)
Thematic Information Extraction: Pattern Recognition
337(70)
Supervised Classification
338(41)
Land-use and Land-cover Classification Schemes
340(10)
Training Site Selection and Statistics Extraction
350(6)
Selecting the Optimum Bands for Image Classification: Feature Selection
356(14)
Select the Appropriate Classification Algorithm
370(9)
Unsupervised Classification
379(10)
Unsupervised Classification Using the Chain Method
379(4)
Unsupervised Classification Using the ISODATA Method
383(2)
Unsupervised Cluster Busting
385(4)
Fuzzy Classification
389(4)
Classification Based on Object-oriented Image Segmentation
393(6)
Object-oriented Image Segmentation and Classification
393(6)
Object-oriented Considerations
399(1)
Incorporating Ancillary Data in the Classification Process
399(2)
Problems Associated with Ancillary Data
399(1)
Approaches to Incorporating Ancillary Data to Improve Remote Sensing Classification Maps
399(2)
References
401(6)
Information Extraction Using Artificial Intelligence
407(24)
Expert Systems
408(13)
Expert System User Interface
408(1)
Creating the Knowledge Base
408(5)
Inference Engine
413(1)
On-line Databases
413(1)
Expert Systems Applied to Remote Sensor Data
413(6)
Advantages of Expert Systems
419(2)
Neural Networks
421(6)
Components and Characteristics of a Typical Artificial Neural Network Used to Extract Information from Remotely Sensed Data
421(4)
Advantages of Artificial Neural Networks
425(1)
Limitations of Artificial Neural Networks
426(1)
Neural Networks versus Expert Systems Developed Using Machine Learning
426(1)
References
427(4)
Thematic Information Extraction: Hyperspectral Image Analysis
431(36)
Multispectral versus Hyperspectral Data Collection
431(2)
Steps to Extract Information from Hyperspectral Data
433(2)
NASA's Airborne Visible/Infrared Imaging Spectrometer
435(1)
Subset Study Area from Flight Line(s)
435(1)
Initial Image Quality Assessment
435(3)
Visual Individual Band Examination
435(2)
Visual Examination of Color Composite Images Consisting of Three Bands
437(1)
Animation
437(1)
Statistical Individual Band Examination
437(1)
Radiometric Calibration
438(5)
In Situ Data Collection
438(1)
Radiosondes
438(1)
Radiative Transfer-based Atmospheric Correction
438(3)
Band-by-Band Spectral Polishing
441(2)
Empirical Line Calibration Atmospheric Correction
443(1)
Geometric Correction of Hyperspectral Remote Sensor Data
443(1)
Reducing the Dimensionality of Hyperspectral Data
443(2)
Minimum Noise Fraction Transformation
444(1)
Endmember Determination: Locating the Spectrally Purest Pixels
445(5)
Pixel Purity Index Mapping
445(2)
n-dimensional Endmember Visualization
447(3)
Mapping and Matching Using Hyperspectral Data
450(7)
Spectral Angle Mapper
450(3)
Subpixel Classification (Linear Spectral Unmixing)
453(3)
Spectroscopic Library Matching Techniques
456(1)
Indices Developed for Hyperspectral Data
457(4)
Normalized Difference Vegetation Index --- NDVI
457(2)
Narrow-band Derivative-based Vegetation Indices
459(1)
Yellowness Index --- YI
459(1)
Physiological Reflectance Index --- PRI
460(1)
Normalized Difference Water Index --- NDWI
460(1)
Red-edge Position Determination --- REP
460(1)
Crop Chlorophyll Content Prediction
461(1)
Derivative Spectroscopy
461(1)
References
462(5)
Digital Change Detection
467(28)
Steps Required to Perform Change Detection
467(7)
Change Detection Geographic Region of Interest
467(1)
Change Detection Time Period
467(1)
Select an Appropriate Land-use/Land-cover Classification System
468(1)
Hard and Fuzzy Change Detection Logic
468(1)
Per-pixel or Object-oriented Change Detection
468(1)
Remote Sensing System Considerations
468(3)
Environmental Considerations of Importance When Performing Change Detection
471(3)
Selection of a Change Detection Algorithm
474(17)
Change Detection Using Write Function Memory Insertion
475(1)
Multidate Composite Image Change Detection
475(3)
Image Algebra Change Detection
478(4)
Post-classification Comparison Change Detection
482(1)
Change Detection Using a Binary Change Mask Applied to Date 2
483(1)
Change Detection Using an Ancillary Data Source as Date 1
483(1)
Spectral Change Vector Analysis
484(2)
Chi-square Transformation Change Detection
486(1)
Cross-correlation Change Detection
486(1)
Knowledge-based Vision Systems for Detecting Change
487(1)
Visual On-screen Change Detection and Digitization
487(4)
Atmospheric Correction for Change Detection
491(1)
When Atmospheric Correction Is Necessary
491(1)
When Atmospheric Correction Is Unnecessary
492(1)
Summary
492(1)
References
492(3)
Thematic Map Accuracy Assessment
495(22)
Land-use and Land-cover Map Accuracy Assessment
495(1)
Sources of Error in Remote Sensing--derived Thematic Products
496(3)
The Error Matrix
499(1)
Training versus Ground Reference Test Information
500(1)
Sample Size
501(1)
Sample Size Based on Binomial Probability Theory
501(1)
Sample Size Based on Multinomial Distribution
501(1)
Sampling Design (Scheme)
502(3)
Simple Random Sampling
504(1)
Systematic Sampling
504(1)
Stratified Random Sampling
504(1)
Stratified Systematic Unaligned Sampling
504(1)
Cluster Sampling
505(1)
Obtaining Ground Reference Information at Locations Using a Response Design
505(1)
Evaluation of Error Matrices
505(7)
Descriptive Evaluation of Error Matrices
505(1)
Discrete Multivariate Analytical Techniques Applied to the Error Matrix
506(2)
Fuzzification of the Error Matrix
508(4)
Geostatistical Analysis to Assess the Accuracy of Remote Sensing--derived Information
512(1)
Image Metadata and Lineage Information for Remote Sensing--derived Products
512(1)
Individual Image Metadata
513(1)
Lineage of Remote Sensing--derived Products
513(1)
References
513(4)
Index 517


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