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Full Description
Remote Sensing and Image Processing in Mineralogy reveals the critical tools required to comprehend the latest technology surrounding the remote sensing imaging of mineralogy, oil and gas explorations. It particularly focusses on multispectral, hyperspectral and microwave radar, as the foremost sources to understand, analyze and apply concepts in the field of mineralogy. Filling the gap between modern physics quantum theory and image processing applications of remote sensing imaging of geological features, mineralogy, oil and gas explorations, this reference is packed with technical details associated with the potentiality of multispectral, hyperspectral and synthetic aperture radar (SAR). The book also includes key methods needed to extract the value-added information necessary, such as lineaments, gold and copper minings. This book also reveals novel speculation of quantum spectral mineral signature identifications, named as quantized Marghany's mineral spectral or Marghany Quantum Spectral Algorithms for Mineral identifications (MQSA).
Rounding out with practical simulations of 4-D open-pit mining identification and monitoring using the hologram radar interferometry technique, this book brings an effective new source of technology and applications for today's minerology and petroleum engineers.
Key Features
• Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data.
• Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data.
• Includes over 200 equations that illustrate how to follow examples in the book.
Contents
1. Principles of Mineralogy, Oil and Gas 2. Quantization of Minerals and their Interactions with Remote Sensing Photons 3. Quantum Computing of Image Processing 4. Quantum Spectral Libraries of Minerals in Optical Remote Sensing Data 5. Quantum Multispectral and Hyperspectral Remote Sensing Imaging of Alteration Minerals 6. Evolving Quantum Image Processing Tool for Lineament Automatic Detection in Optical Remote Sensing Satellite Data 7. Quantum Support Vector Machine in Retrieving Clay Mineral Saturation in Multispectral Sentinel-2 Satellite Data 8. Automatic Detection of Oil Seeps in Synthetic Aperture Radar Using Quantum Immune Fast Spectral Clustering 9. Quantum Interferometry Radar for Oil and Gas Explorations 10. Quantum Machine Learning Algorithm for Iron, Gold, and Copper Detection in Optical Remote Sensing Data 11. Four-Dimensional Hologram Interferometry for Automatic Detection of Copper Mineralization Using Terrasar-X Satellite Data
