Computer processing of remotely-sensed images : an introduction /

Computer processing of remotely-sensed images : an introduction /

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Bibliographic Details
Author / Creator:Mather, Paul M.
Imprint:Chichester ; New York : Wiley, c1987.
Description:xiii, 352 p. : ill. ; 24 cm.
Language:English
Subject:Remote sensing -- Data processing
Image processing -- Digital techniques.
Remote sensing -- Data processing.
Remote-sensing images.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/870751
Hidden Bibliographic Details
ISBN:0471906484 : $47.00
Notes:Includes index.
Bibliography: p. 332-346.
Table of Contents:
  • Preface to the First Edition
  • Preface to the Second Edition
  • Preface to the Third Edition
  • List of Examples
  • 1. Remote Sensing: Basic Principles
  • 1.1. Introduction
  • 1.2. Electromagnetic radiation and its properties
  • 1.2.1. Terminology
  • 1.2.2. Nature of electromagnetic radiation
  • 1.2.3. The electromagnetic spectrum
  • 1.2.4. Sources of electromagnetic radiation
  • 1.2.5. Interactions with the Earth's atmosphere
  • 1.3. Interaction with Earth-surface materials
  • 1.3.1. Introduction
  • 1.3.2. Spectral reflectance of Earth surface materials
  • 1.4. Summary
  • 2. Remote Sensing Platforms and Sensors
  • 2.1. Introduction
  • 2.2. Characteristics of imaging remote sensing instruments
  • 2.2.1. Spatial resolution
  • 2.2.2. Spectral resolution
  • 2.2.3. Radiometric resolution
  • 2.3. Optical, near-infrared and thermal imaging sensors
  • 2.3.1. Along-Track Scanning Radiometer (ATSR
  • 2.3.2. Advanced Very High Resolution Radiometer (AVHRR
  • 2.3.3. MODIS MODerate Resolution Imaging Spectrometer
  • 2.3.4. Ocean observing instruments
  • 2.3.5. IRS-1 LISS
  • 2.3.6. Landsat Instruments
  • 2.3.7. SPOT sensors
  • 2.3.8. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER
  • 2.3.9. High-resolution commercial and micro-satellite systems
  • 2.4. Microwave imaging sensors
  • 2.4.1. ERS SAR
  • 2.4.2. RADARSAT
  • 2.5. Summary
  • 3. Hardware and Software Aspects of Digital Image Processing
  • 3.1. Introduction
  • 3.2. Properties of digital remote sensing data
  • 3.2.1. Digital data
  • 3.2.2. Data formats
  • 3.2.3. System processing
  • 3.3. MIPS software
  • 3.3.1. Installing MIPS
  • 3.3.2. Using MIPS
  • 3.3.3. Summary of MIPS functions
  • 3.4. Summary
  • 4. Pre-processing of Remotely Sensed Data
  • 4.1. Introduction
  • 4.2. Cosmetic operations
  • 4.2.1. Missing scan lines
  • 4.2.2. De-striping methods
  • 4.3. Geometric correction and registration
  • 4.3.1. Orbital geometry model
  • 4.3.2. Transformation based on ground control points
  • 4.3.3. Resampling procedures
  • 4.3.4. Image registration
  • 4.3.5. Other geometric correction methods
  • 4.4. Atmospheric correction
  • 4.4.1. Background
  • 4.4.2. Image-based methods
  • 4.4.3. Radiative transfer models
  • 4.4.4. Empirical line method
  • 4.5. Illumination and view angle effects
  • 4.6. Sensor calibration
  • 4.7. Terrain effects
  • 4.8. Summary
  • 5. Image Enhancement Techniques
  • 5.1. Introduction
  • 5.2. Human visual system
  • 5.3. Contrast enhancement
  • 5.3.1. Linear contrast stretch
  • 5.3.2. Histogram equalisation
  • 5.3.3. Gaussian Stretch
  • 5.4. Pseudocolour enhancement
  • 5.4.1. Density slicing
  • 5.4.2. Pseudocolour transform
  • 5.5. Summary
  • 6. Image Transforms
  • 6.1. Introduction
  • 6.2. Arithmetic operations
  • 6.2.1. Image addition
  • 6.2.2. Image subtraction
  • 6.2.3. Image multiplication
  • 6.2.4. Image division and vegetation Indices
  • 6.3. Empirically based image transforms
  • 6.3.1. Perpendicular Vegetation Index
  • 6.3.2. Tasselled Cap (Kauth-Thomas) transformation
  • 6.4. Principal Components Analysis
  • 6.4.1. Standard Principal Components Analysis
  • 6.4.2. Noise-adjusted Principal Components Analysis
  • 6.4.3. Decorrelation stretch
  • 6.5. Hue, Saturation and Intensity (HIS) transform
  • 6.6. The Discrete Fourier Transform
  • 6.6.1. Introduction
  • 6.6.2. Two-dimensional DFT
  • 6.6.3. Applications of the DFT
  • 6.7. The Discrete Wavelet Transform
  • 6.7.1. Introduction
  • 6.7.2. The one-dimensional Discrete Wavelet Transform
  • 6.7.3. The two-dimensional Discrete Wavelet Transform
  • 6.8. Summary
  • 7. Filtering Techniques
  • 7.1. Introduction
  • 7.2. Spatial domain low-pass (smoothing) filters
  • 7.2.1. Moving average filter
  • 7.2.2. Median filter
  • 7.2.3. Adaptive filters
  • 7.3. Spatial domain high-pass (sharpening) filters
  • 7.3.1. Image subtraction method
  • 7.3.2. Derivative-based methods
  • 7.4. Spatial domain edge detectors
  • 7.5. Frequency domain filters
  • 7.6. Summary
  • 8. Classification
  • 8.1. Introduction
  • 8.2. Geometrical basis of classification
  • 8.3. Unsupervised classification
  • 8.3.1. The k-means algorithm
  • 8.3.2. ISODATA
  • 8.3.3. A modified k-means algorithm
  • 8.4. Supervised classification
  • 8.4.1. Training samples
  • 8.4.2. Statistical classifiers
  • 8.4.3. Neural Classifiers
  • 8.5. Fuzzy classification and linear spectral unmixing
  • 8.5.1. The linear mixture model
  • 8.5.2. Fuzzy classifiers
  • 8.6. Other approaches to image classification
  • 8.7. Incorporation of non-spectral features
  • 8.7.1. Texture
  • 8.7.2. Use of external data
  • 8.8. Contextual information
  • 8.9. Feature selection
  • 8.10. Classification accuracy
  • 8.11. Summary
  • 9. Advanced Topics
  • 9.1. Introduction
  • 9.2. SAR Interferometry
  • 9.2.1. Basic principles
  • 9.2.2. Interferometric processing
  • 9.2.3. Problems in SAR interferometry
  • 9.2.4. Applications of SAR interferometry
  • 9.3. Imaging spectrometry
  • 9.3.1. Introduction
  • 9.3.2. Processing imaging spectrometer data
  • 9.4. Lidar
  • 9.4.1. Introduction
  • 9.4.2. Lidar details
  • 9.4.3. Lidar applications
  • 9.5. Summary
  • Appendix A. Using the CD-ROM Image Data Sets
  • References
  • Index

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