Hyperspectral Imaging

Hyperspectral Imaging, Volume 32, presents a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of applications in different scientific and industrial areas. This book presents, for the first time, a comprehensive collection of the main multivariate algorithms used for hyperspectral image analysis in different fields of application. The benefits, drawbacks and suitability of each are fully discussed, along with examples of their application. Users will find state-of-the art information on the machinery for hyperspectral image acquisition, along with a critical assessment of the usage of hyperspectral imaging in diverse scientific fields. Provides a comprehensive roadmap of hyperspectral image analysis, with benefits and considerations for each method discussed Covers state-of-the-art applications in different scientific fields Discusses the implementation of hyperspectral devices in different environments

Produk Detail:

  • Author : Jose Manuel Amigo
  • Publisher : Data Handling in Science and T
  • Pages : 450 pages
  • ISBN : 9780444639776
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKHyperspectral Imaging

Hyperspectral Imaging

Hyperspectral Imaging
  • Author : Anonim
  • Publisher : Elsevier
  • Release : 29 September 2019
GET THIS BOOKHyperspectral Imaging

Hyperspectral Imaging, Volume 32, presents a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of applications in different scientific and industrial areas. This book presents, for the first time, a comprehensive collection of the main multivariate algorithms used for hyperspectral image analysis in different fields of application. The benefits, drawbacks and suitability of each are fully discussed, along with examples of their application. Users will find state-of-the art information on the machinery for hyperspectral

The Future of Hyperspectral Imaging

The Future of Hyperspectral Imaging
  • Author : Stefano Selci
  • Publisher : MDPI
  • Release : 20 November 2019
GET THIS BOOKThe Future of Hyperspectral Imaging

This book includes some very recent applications and the newest emerging trends of hyper-spectral imaging (HSI). HSI is a very recent and strange beast, a sort of a melting pot of previous techniques and scientific interests, merging and concentrating the efforts of physicists, chemists, botanists, biologists, and physicians, to mention just a few, as well as experts in data crunching and statistical elaboration. For almost a century, scientific observation, from looking to planets and stars down to our own cells

Hyperspectral Image Analysis

Hyperspectral Image Analysis
  • Author : Saurabh Prasad,Jocelyn Chanussot
  • Publisher : Springer Nature
  • Release : 27 April 2020
GET THIS BOOKHyperspectral Image Analysis

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in

Hyperspectral Imaging

Hyperspectral Imaging
  • Author : Chein-I Chang
  • Publisher : Springer Science & Business Media
  • Release : 11 December 2013
GET THIS BOOKHyperspectral Imaging

Hyperspectral Imaging: Techniques for Spectral Detection and Classification is an outgrowth of the research conducted over the years in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. It explores applications of statistical signal processing to hyperspectral imaging and further develops non-literal (spectral) techniques for subpixel detection and mixed pixel classification. This text is the first of its kind on the topic and can be considered a recipe book offering various techniques for

Hyperspectral Imaging Technology in Food and Agriculture

Hyperspectral Imaging Technology in Food and Agriculture
  • Author : Bosoon Park,Renfu Lu
  • Publisher : Springer
  • Release : 29 September 2015
GET THIS BOOKHyperspectral Imaging Technology in Food and Agriculture

Hyperspectral imaging or imaging spectroscopy is a novel technology for acquiring and analysing an image of a real scene by computers and other devices in order to obtain quantitative information for quality evaluation and process control. Image processing and analysis is the core technique in computer vision. With the continuous development in hardware and software for image processing and analysis, the application of hyperspectral imaging has been extended to the safety and quality evaluation of meat and produce. Especially in

Hyperspectral Imaging for Food Quality Analysis and Control

Hyperspectral Imaging for Food Quality Analysis and Control
  • Author : Da-Wen Sun
  • Publisher : Elsevier
  • Release : 29 June 2010
GET THIS BOOKHyperspectral Imaging for Food Quality Analysis and Control

Based on the integration of computer vision and spectrscopy techniques, hyperspectral imaging is a novel technology for obtaining both spatial and spectral information on a product. Used for nearly 20 years in the aerospace and military industries, more recently hyperspectral imaging has emerged and matured into one of the most powerful and rapidly growing methods of non-destructive food quality analysis and control. Hyperspectral Imaging for Food Quality Analysis and Control provides the core information about how this proven science can be

Hyperspectral Imaging Analysis and Applications for Food Quality

Hyperspectral Imaging Analysis and Applications for Food Quality
  • Author : N.C. Basantia,Leo M.L. Nollet,Mohammed Kamruzzaman
  • Publisher : CRC Press
  • Release : 16 November 2018
GET THIS BOOKHyperspectral Imaging Analysis and Applications for Food Quality

In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for

Hyperspectral Imaging in Agriculture, Food and Environment

Hyperspectral Imaging in Agriculture, Food and Environment
  • Author : Alejandro Isabel Luna Maldonado,Humberto Rodriguez-Fuentes,Juan Antonio Vidales Contreras
  • Publisher : BoD – Books on Demand
  • Release : 01 August 2018
GET THIS BOOKHyperspectral Imaging in Agriculture, Food and Environment

This book is about the novel aspects and future trends of the hyperspectral imaging in agriculture, food, and environment. The topics covered by this book are hyperspectral imaging and their applications in the nondestructive quality assessment of fruits and vegetables, hyperspectral imaging for assessing quality and safety of meat, multimode hyperspectral imaging for food quality and safety, models fitting to pattern recognition in hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization method to

Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences

Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences
  • Author : Michael Vohland,András Jung
  • Publisher : MDPI
  • Release : 14 May 2021
GET THIS BOOKHyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences

The aim of the Special Issue “Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences” was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of

Hyperspectral Imaging

Hyperspectral Imaging
  • Author : Chein-I Chang
  • Publisher : Springer Science & Business Media
  • Release : 31 July 2003
GET THIS BOOKHyperspectral Imaging

Explores the application of statistical signal processing to hyperspectral imaging and further develops non-literal (spectral) techniques for subpixel detection and mixed pixel classification. This text is the first of its kind on the topic anc can be considered a recipe book offering various techniques for hyperspectral data exploitation.

Hyperspectral Image Processing

Hyperspectral Image Processing
  • Author : Liguo Wang,Chunhui Zhao
  • Publisher : Springer
  • Release : 15 July 2015
GET THIS BOOKHyperspectral Image Processing

Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data
  • Author : Pramod K. Varshney,Varshney Pramod K.,Manoj K. Arora
  • Publisher : Springer Science & Business Media
  • Release : 12 August 2004
GET THIS BOOKAdvanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

The main objective of this book is to apprise the reader of the use of a number of tools and techniques for a variety of image processing tasks, namely Independent Component Analysis (ICA), Mutual Information (MI), Markov Random Field (MRF) Models and Support Vector Machines (SVM). Typical applications considered are feature extraction, image classification, image fusion and change detection. The book also treats a number of experimental examples based on a variety of remote sensors.The utility of the book

Deep Learning for Hyperspectral Image Analysis and Classification

Deep Learning for Hyperspectral Image Analysis and Classification
  • Author : Linmi Tao,Atif Mughees
  • Publisher : Springer Nature
  • Release : 20 February 2021
GET THIS BOOKDeep Learning for Hyperspectral Image Analysis and Classification

This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervised spectral-spatial adaptive band-noise factor-based formulation is devised for HSI noise detection and band categorization. The method to characterize the bands along with the noise estimation of HSIs will benefit subsequent remote sensing techniques significantly. This book develops on two fronts: On the one hand, it is aimed at domain professionals who want to have an updated overview of how hyperspectral acquisition techniques can combine with deep learning