Imaging Spectroscopy for Scene Analysis
|Published:||Oct 31 2012|
|Posted:||Jul 23 2016|
|Book size:||3.64 MB|
This book presents a detailed analysis of spectral imaging, describing how it can be used for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications. Features: discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation; examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery; describes spectrum representations for the interpolation of reflectance and radiance values, and the classification of spectra; reviews the use of imaging spectroscopy for material identification; explores the recovery of reflection geometry from image reflectance; investigates spectro-polarimetric imagery, and the recovery of object shape and material properties using polarimetric images captured from a single view.
Methodologies, Tools, and Techniques for Incident Analysis and Response
Nearly every business depends on its network to provide information services to carry out essential activities, and network intrusion attacks have been growing increasingly frequent and severe. When network intrusions do occur, it's imperative that a thorough and systematic analysis and investigation of the attack is conducted to determine the nature of the threat and the extent of information lost, stolen, or damaged during the attack. A thorough and timely investigation and response can serve to minimize network downtime and ensure that critical business systems are maintained in full operation. Network Intrusion Analysis teaches the reader about the various tools and techniques to use during a network intrusion investigation. The book focuses on t...
Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary devel...
Practical Recipes for Design, Analysis and Implementation
The Most Complete, Modern, and Useful Collection of DSP Recipes: More Than 50 Practical Solutions and More than 30 Summaries of Pertinent Mathematical Concepts for Working Engineers Notes on Digital Signal Processing is a comprehensive, easy-to-use collection of step-by-step procedures for designing and implementing modern DSP solutions. Leading DSP expert and IEEE Signal Processing Magazine associate editor C. Britton Rorabaugh goes far beyond the basic procedures found in other books while providing the supporting explanations and mathematical materials needed for a deeper understanding. Rorabaugh covers the full spectrum of challenges working engineers are likely to encounter and delves into crucial DSP nuances discussed nowhere else. Reader...
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