Name: Computer Processing of Remotely-sensed Images By P.M. Mather
SKU: 9780470849187
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Computer Processing of Remotely-sensed Images Summary

Computer Processing of Remotely-sensed Images: An Introduction by P.M. Mather

Remotely-sensed images of the Earth's surface provide a valuable source of information about the geographical distribution and properties of natural and cultural features. This fully revised and updated edition of a highly regarded textbook deals with the mechanics of processing remotely-sensed images. Presented in an accessible manner, the book covers a wide range of image processing and pattern recognition techniques. The features include: new topics on LiDAR data processing, SAR interferometry, the analysis of imaging spectrometer image sets and the use of the wavelet transform. The accompanying CD-ROM comes with: updated MIPS software, including modules for standard procedures such as image display, filtering, image transforms, graph plotting, import of data from a range of sensors; a set of exercises, including data sets, illustrating the application of discussed methods using the MIPS software; and, an extensive list of WWW resources including colour illustrations for easy download.

About P.M. Mather

Paul Mather has been Professor of Geographical Information Science at The University of Nottingham, UK since 1988. BA (Cambridge), PhD (Nottingham). Main research interests: multivariate analysis of spatial data (Computational Methods of Multivariate Analysis in Physical Geography, Chichester, John Wiley, 1976) and digital image processing applied to remotely sensed data, particularly algorithms for classification and pattern recognition (Classification Methods for Remotely Sensed Data, with B. Tso, London, Taylor and Francis, 2001). * Awarded OBE in the Queen's Jubilee Honours in 2002 for 'services to remote sensing and photogrammetry'. * Recipient of The Remote Sensing Society's Gold Medal in 1996. * Presented with the Back Award of the Royal Geographical Society for 'contributions to remote sensing' in 1992. * Winner of the Dearing Award for Outstanding contribution to the development of teaching and learning, The University of Nottingham, 2003. * Invited speaker/lecturer at conferences/courses all over the world (e.g., Japan, Indonesia, India, South Africa, Poland, Hungary, Bulgaria, Spain).

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.

Additional information

Sku

GOR013276723

ISBN 13

9780470849187

ISBN 10

0470849185

Title

Computer Processing of Remotely-sensed Images: An Introduction by P.M. Mather

Author

P.M. Mather

Condition

Used - Very Good

Binding type

Hardback

Publisher

John Wiley and Sons Ltd

Year published

20040427

Number of pages

442

Prizes

N/A

Cover note

Book picture is for illustrative purposes only, actual binding, cover or edition may vary.

Note

This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

Computer Processing of Remotely-sensed Images P.M. Mather

Computer Processing of Remotely-sensed Images by P.M. Mather

Summary

Computer Processing of Remotely-sensed Images Summary

Computer Processing of Remotely-sensed Images: An Introduction by P.M. Mather

About P.M. Mather

Table of Contents

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