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 modelling. The book includes detailed algorithms to enable readers to better understand and implement the 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 modelling, remote sensing and aquatic science, as well as geographers, geophysicists, and environmental engineers
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Dedication - p. vi 7. Preface - p. xiii 8. Chapter 1. Nonlinearity: fundamental concepts and understanding - p. 1 9. Chapter 2. Unraveling the mysteries: Ocean turbulence and front dynamics - p. 23 10. Chapter 3. Quantized synthetic aperture radar signal: a comprehensive exploration - p. 51 11. Chapter 4. Quantized Marghany turbulence boundary in the South China Sea by using SAR data - p. 89 12. Chapter 5. Automatic detection of internal wave in quantized Marghany turbulence boundary in SAR data - p. 119 13. Chapter 6. Quantized Marghany oceanic front detection in MultiSAR datasets: unveiling the hidden patterns of the South China Sea - p. 149 14. Chapter 7. Texture and quantum entropy algorithms for turbulence and oceanic front structural detections in synthetic aperture radar images - p. 195 15. Chapter 8. Developing a novel quantum cluster algorithm for the automatic detection of spiral patterns in SAR data - p. 231 16. Chapter 9. Fractal dimension algorithm for automatic detection of oceanic front and turbulence structural in MultiSAR data - p. 261 17. Chapter 10. Quantum finite automaton-based algorithm for identifying rain cell turbulences in synthetic aperture radar images - p. 283 18. Chapter 11. Quantum cellular automata algorithm for automatic detection of upwelling in synthetic aperture radar data - p. 303 19. Chapter 12. Quantum multiobjective algorithm for detecting turbulence vorticity and eddies in synthetic aperture radar satellite data - p. 337 20. Chapter 13. Four-dimensional quantum holographic interferometry radar for nonlinear shear-wave chaotic flow detection - p. 363 21. Index - p. 387
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 modelling. The book includes detailed algorithms to enable readers to better understand and implement the 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 modelling, remote sensing and aquatic science, as well as geographers, geophysicists, and environmental engineers
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Dedication - p. vi 7. Preface - p. xiii 8. Chapter 1. Nonlinearity: fundamental concepts and understanding - p. 1 9. Chapter 2. Unraveling the mysteries: Ocean turbulence and front dynamics - p. 23 10. Chapter 3. Quantized synthetic aperture radar signal: a comprehensive exploration - p. 51 11. Chapter 4. Quantized Marghany turbulence boundary in the South China Sea by using SAR data - p. 89 12. Chapter 5. Automatic detection of internal wave in quantized Marghany turbulence boundary in SAR data - p. 119 13. Chapter 6. Quantized Marghany oceanic front detection in MultiSAR datasets: unveiling the hidden patterns of the South China Sea - p. 149 14. Chapter 7. Texture and quantum entropy algorithms for turbulence and oceanic front structural detections in synthetic aperture radar images - p. 195 15. Chapter 8. Developing a novel quantum cluster algorithm for the automatic detection of spiral patterns in SAR data - p. 231 16. Chapter 9. Fractal dimension algorithm for automatic detection of oceanic front and turbulence structural in MultiSAR data - p. 261 17. Chapter 10. Quantum finite automaton-based algorithm for identifying rain cell turbulences in synthetic aperture radar images - p. 283 18. Chapter 11. Quantum cellular automata algorithm for automatic detection of upwelling in synthetic aperture radar data - p. 303 19. Chapter 12. Quantum multiobjective algorithm for detecting turbulence vorticity and eddies in synthetic aperture radar satellite data - p. 337 20. Chapter 13. Four-dimensional quantum holographic interferometry radar for nonlinear shear-wave chaotic flow detection - p. 363 21. Index - p. 387
