Image Processing for Remote Sensing
CRC Press, Oct 17, 2007 - Technology & Engineering - 400 pages
Edited by leaders in the field, with contributions by a panel of experts, Image Processing for Remote Sensing explores new and unconventional mathematics methods. The coverage includes the physics and mathematical algorithms of SAR images, a comprehensive treatment of MRF-based remote sensing image classification, statistical approaches for improved classification with the remote sensing data, Wiener filter-based method, and other modern approaches and methods of image processing for remotely sensed data.
Each chapter explores a technique for dealing with a specific remote sensing problem. The book offers physical insights on the steps for constructing various digital seismic images. The volume examines image modeling, statistical image classifiers, change detection, independent component analysis, vertex component analysis, image fusion for better classification. It explores unique topics such as accuracy assessment and information-theoretic measure of multiband images and many chapters emphasize issues with synthetic aperture radar (SAR) images.
Continued development on imaging sensors creates new opportunities and challenges in image processing for remote sensing. Image Processing for Remote Sensing not only presents the most up to date developments of image processing for remote sensing but also suggests to readers the many challenging problems ahead for further study.
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MRFBased RemoteSensing Image Classification with Automatic Model Parameter Estimation
Random Forest Classification of Remote Sensing Data
Supervised Image Classification of MultiSpectral Images Based on Statistical Machine Learning
Unsupervised Change Detection in MultiTemporal SAR Images
ChangeDetection Methods for Location of Mines in SAR Imagery
Vertex Component Analysis A GeometricBased Approach to Unmix Hyperspectral Data
Two ICA Approaches for SAR Image Enhancement
Spatial Techniques for Image Classification
Data Fusion for RemoteSensing Applications
The Hermite Transform An Efficient Tool for Noise Reduction and Image Fusion in RemoteSensing
MultiSensor Approach to Automated Classification of Sea Ice Image Data
Use of the BradleyTerry Model to Assess Uncertainty in an Error Matrix from a Hierarchical Segmentation of an ASTER Image
SAR Image Classification by Support Vector Machine
LongRange Dependence Models for the Analysis and Discrimination of SeaSurface Anomalies in Sea SAR Imagery