Synthetic Aperture Radar Image Processing Algorithms for Nonlinear Oceanic Turbulence and Front Modelling is both a research and practice-based reference that bridges the gap between the remote sensing field and the dynamic oceanography exploration field. In this perspective, the book explicates how to apply techniques in synthetic aperture radar and quantum interferometry synthetic aperture radar (QInSAR) for oceanic turbulence and front simulation and modeling. It includes detailed algorithms to enable readers to better understand and implement practices covered in their own work and apply QInSAR to their own research.
This multidisciplinary reference is useful for researchers and academics in dynamic oceanography and modeling, remote sensing and aquatic science, as well as geographers, geophysicists, and environmental engineers.
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Table of Contents
1. An Introduction to Oceanic Turbulence and Fronts
2. Structural oceanic Front Associations with Turbulence
3. Conventional Exploration Methods in Physical Oceanography
4. Overview of Remote Sensing for Turbulence and Oceanic Fronts
5. Mechanism of Microwave Remote Sensing in Geological Structure Imaging
6. Turbulence and Oceanic Front structurals observed under the Polarized Microwave Remote Sensing
7. Texture and Quantum Entropy Algorithms for Turbulence and Oceanic Front structural Detections in Synthetic Aperture Radar Images
8. Mahalanobis Classifier and Neural Network Algorithms For Turbulence Structural Detections
9. Fractal Dimension Algorithm for Automatic Detection of Oceanic Front Structurals
10. Quantum Wavelet Transform for Eddy Structural In SAR Images
11. Quantum Cellular Automata Algorithm for Automatic Detection of Upwelling
12. Quantum Multiobjective Algorithm for Vorticity Detection from Synthetic Aperture Radar
13. Quantum Interferometry Radar for Turbulence Chaotic Flow Simulation
