1st Edition

Automatic Detection Algorithms of Oil Spill in Radar Images

By Maged Marghany Copyright 2020
    312 Pages 10 Color & 203 B/W Illustrations
    by CRC Press

    310 Pages 10 Color & 203 B/W Illustrations
    by CRC Press

    324 Pages 10 Color & 203 B/W Illustrations
    by CRC Press

    Synthetic Aperture Radar Automatic Detection Algorithms (SARADA) for Oil Spills conveys the pivotal tool required to fully comprehend the advanced algorithms in radar monitoring and detection of oil spills, particularly quantum computing and algorithms as a keystone to comprehending theories and algorithms behind radar imaging and detection of marine pollution. Bridging the gap between modern quantum mechanics and computing detection algorithms of oil spills, this book contains precise theories and techniques for automatic identification of oil spills from SAR measurements. Based on modern quantum physics, the book also includes the novel theory on radar imaging mechanism of oil spills.



    With the use of precise quantum simulation of trajectory movements of oil spills using a sequence of radar images, this book demonstrates the use of SARADA for contamination by oil spills as a promising novel technique.



    Key Features:





    • Introduces basic concepts of a radar remote sensing.


    • Fills a gap in the knowledge base of quantum theory and microwave remote sensing.


    • Discusses the important aspects of oil spill imaging in radar data in relation to the quantum theory.


    • Provides recent developments and progresses of automatic detection algorithms of oil spill from radar data.


    • Presents 2-D oil spill radar data in 4-D images.

    Microwave Remote Sensing based on Maxwell Equations
    Maxwell’s Equations
    Simple wave Equation Based on Maxwell’s Equations
    Solution of Electromagnetic Waves in a Homogenous Dielectric
    Electromagnetic Wave Characteristics Based on Maxwell’s Equations
    The Poynting Theory
    Waves from Localized Sources
    Momentum as the Route of  Radiation Pressure
    Can Maxwell’s Electrodynamics Formulate in Space and Time?

    Quantization of Maxwell’s Equation and Electromagnetic Field
    Definitions of Quantization of Electromagnetic Field
    Quantum Radiation
    The Photoelectric Effect
    De Broglie's wavelength
    Quantum Electrodynamics
    Force Carriers
    Maxwell Photon Wave Function
    Quantanize of Electromagnetic Waves
    Feynman's Perspective of Electromagnetic Waves
    Feynman’s Derivation of Maxwell’s Equations
    Photon Spins
    Do Maxwell's Equation Describe a Single Photon or an Infinite Number of Photons?

    Quantum Signals at Microwave Devices
    Electromagnetic Wave and Microwave Beam
    Photon of Microwave Beams
    Concept of Generating Microwave Beams
    Josephson junctions for Microwave Photon Generations
    Mathematical Description of  Quantum Microwave
    Microwave Signal Harmonic Oscillators Using Ladder Operator
    Quantum Electromagnetic Signals Propagating along Transmission Lines
    Quantum Langevin Equation

    Quantum Mechanical of Scattering Cross-Section Theory
    Definitions of Scattering
    Mathematical Description of Scattering Cross-Section
    Why Does Scattering Rely on Spin?
    Correlation between the Scattering Cross-section to the Wave Function
    Scattering from Roughness Surface
    Scattering of Identical Particles
    Scattering of Particles with Spin
    Scattering of Zero Spin Particles
    Resonant Scattering
    Dielectric Materials and Electric Polarizability
    Atom-Photon Scattering
    Quantum Young Scattering

    Quantization of Radar Theory
    Radio Detecting And Ranging
    Echo-location Detecting and Ranging
    High-Range-Resolution (HRR) Imaging
    Radar Microwave Characteristics
    Why Quantum Radar Sensors Are Required?
    What Does Mean by Quantum Radar?
    What are the Classifications of Quantum Radar?
    Classical Radar Equation
    Quantum Radar Equation
    Radar Scattering Regime
    Quantum Theory of Radar System
    Quantum Radar Illumination

    Theories of Synthetic Aperture Radar
    What is Meant by Aperture?
    Antenna Aperture
    Real and Synthetic Aperture Radar
    Radar Resolution
    Spatial Resolution
    Slant and Ground Range Resolution
    Resolution Cell
    Ambiguous Range
    Range-Rate Measurement (Doppler)
    Ambiguity Function  of SAR
    SAR Pulse Compression Waveforms
    Range Compression
    Azimuth Compression
    Azimuth Matched Filtering
    Speckles
    SAR Satellite Sensors
    Waves and Frequency Ranges Used by Radar

    Novel Relativity Theories of Synthetic Aperture Radar
    What is Simple Definition of Relativity?
    Relativistic of SAR Doppler
    Time Dilation
    Length Contraction
    Does SAR  Polarization Cause Length Contraction?
    SAR Time and Range Relativities
    The relativity of Frequency Changing
    Invariance of Space-time Interval

    Quantization of Oil Spill Imagining in Synthetic Aperture Radar
    Quantization of Crude Oil  Chemical Chains
    Wave Particle Duality of Oil Spill
    Quantum of Oil Spill Electric Conductivity
    Bragg Scattering and Dielectric Sea Surface
    Impact of Surface Dielectric in SAR Backscatter
    Quantization Specular Reflection in SAR Data
    Quantum Radar Cross Section of Bragg Scattering of Oil-Covered
    Decoherence Imaging Mechanism of Oil Spill

    Texture and Quantum Entropy Algorithms for Oil Spill Detection in Synthetic Aperture Radar Images
    Textures Based-SAR Backscattering from Oil-covered Water
    Texture Algorithms
    Structure of the GLCM
    Creating Texture Image
    Mathematical Description of Co-occurrence Matrix
    Can GLCM  Accurately Detect Oil Spill?
    Can Quantum Entropy perform better than Entropy for the Automatic Detection of Oil Spill?

    Mahalanobis Classifier and Neural Network Algorithms for Oil Spill Detection
    Machine Learning Algorithms for Automatic Detection of Oil Spill
    Hypotheses
    Selected  SAR Data Acquisition
    Mahalanobis Algorithm
    Oil Spill Detection by Mahalanobis Classifier
    Artificial Intelligent for Oil Spill Automatic Detection
    Frame Structure of Neural Network for Oil Spill  Automatic Detection
    Backpropagation Learning Algorithm for Automatic Detection of Oil Spill
    Backpropagation Training Algorithm
    Oil Spill Detection by Neural Network Algorithm
    Comparison between Mahalanobis Classifier and Neural Networks

    Fractal Algorithm for Discrimination between Oil Spill and Look-Alike
    Definitions of Fractal
    Fractal Dimensions
    Estimation of Fractal
    Estimation of Hurst Exponent
    Fractal Algorithm for  Oil Spill Identification
    Otsu Thresholding Algorithm
    Examined SAR Satellite Data
    Backscatter, Incident Angle and Wind Variation along Suspected Oil Spill Patches
    Fractal Map of Oil Spill and Look-alikes
    How Far Can Fractal Algorithm Detect Oil Spill?

    Quantum Cellular Automata Algorithm for Automatic Detection of Oil Spills and Look-Alikes
    Principles of Quantum-dot Cellular Automata
    Quantum Cellular Automata Cell Construction
    QCA Adder with Five Gates for Automatic Detection of Oil Spill
    Cellular automata for Automatic Detection of Oil Spill
    Explored SAR Images
    Oil Spills in RADARSAT-2 SAR Data
    Automatic Detection of Oil Spill by Quantum Cellular Automata
    Accuracy of QCA for Automatic Detection of Oil Spill  in SAR Data
    Why QCA  is able to Detect Oil Spill Automatically?
    Quantum Multiobjective Algorithm for Automatic Detection of Oil Spill Spreading from Full Polarimetric Sar Data
    Principles of Fully Polarimetric SAR Images
    Quantum Computing
    Quantum Machine Learning
    Quantum Multiobjective Evolutionary Algorithm (QMEA)
    Generation of Qubit Populations
    Generation of Oil Spill Population Pattern
    Quantum Non-dominate Sort and Elitism (QNSGA-II)
    Quantum Pareto Optimal Solution
    Automatic Detection of Oil Spill in Full Polarimetric SAR
    Applications of QNSGA-II to other Satellite Polarimetric SAR Sensors
    Quantum Decoherence Theory and QNSGA-II
    Pareto Optimization Role in QNSGA-II
    Comparison with Previous Studies

    Simulation of Trajectory Movements of Oil Spill in Multisar Satellite Data Using Quantum Hopfield Algorithm
    Oil Spill Trajectory Models:  What They Are, How They Are Created, How They Are Used An Oil Spill?
    Role of Synthetic Aperture Radar for Tracking Oil Spill Trajectory Movement
    Hypotheses and Objectives
    Fay ‘s  Algorithm and Trajectory of Oil Spill
    Hopfield Neural Network for Retrieving Current Pattern from MultiSAR Data
    Quantum Hopfield Algorithm
    Quantum Trajectory Search for Oil Spill Movements in MultiSAR Data
    Sequences of SAR Data for Oil Spill Trajectory Movements
    Trajectory Movements of Oil Spill Using Quantum Hopfield Algorithm
    Impact of Current Pattern on Oil Spill Trajectory Movements
    How far the Impact of Loop Current on Oil Spill?
    Why qHop Algorithm can be used to simulate and track the oil spill trajectory movement?

     

     

     

    Biography

    Maged Marghany is currently a professor of remote sensing in the Faculty of Geospatial and Real Estate, Geomatika University College (GUC), Malaysia. He authored Advanced Remote Sensing Technology for Tsunami Modelling and Forecasting, published in 2018. His research focuses on microwave remote sensing and remote sensing for mineralogy detection and mapping. Previously, he worked as a Deputy Director in Research and Development at the Institute of Geospatial Science and Technology and the Department of Remote Sensing, both at Universiti Teknologi Malaysia. Maged has earned many degrees, including a post-doctoral in radar remote sensing from the International Institute for Aerospace Survey and Earth Sciences, a PhD in environmental remote sensing from the Universiti Putra Malaysia, a Master of Science in physical oceanography from the University Pertanian Malaysia, general and special diploma of Education and a Bachelor of Science in physical oceanography from the University of Alexandria in Egypt. Maged has published well over 250 papers in international conferences and journals and is active in International Geoinformatics, and the International Society for Photogrammetry and Remote Sensing (ISPRS).