hyperspectral imaging

Hyperspectral Imaging
Author: Chein-I Chang
Publisher: Springer Science & Business Media
Release Date: 2013-12-11
Pages: 370
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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 data exploitation. In particular, some known techniques, such as OSP (Orthogonal Subspace Projection) and CEM (Constrained Energy Minimization) that were previously developed in the RSSIPL, are discussed in great detail. This book is self-contained and can serve as a valuable and useful reference for researchers in academia and practitioners in government and industry.

Hyperspectral Imaging
Author:
Publisher: Elsevier
Release Date: 2019-09-29
Pages: 800
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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

The Future Of Hyperspectral Imaging
Author: Stefano Selci
Publisher: MDPI
Release Date: 2019-11-20
Pages: 220
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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 and below, could be divided into two main categories: analyzing objects on the basis of their physical dimension (recording size, position, weight, etc. and their variations) or on how the object emits, reflects, or absorbs part of the electromagnetic spectrum, i.e., spectroscopy. While the two aspects have been obviously entangled, instruments and skills have always been clearly distinct from each other. With HSI now available, this is no longer the case. This instrument can return specimen dimensionalities and spectroscopic properties to any single pixel of your specimen, in a single set of data. HSI modality is ubiquitous and scale-invariant enough to be used to mark terrestrial resources on the basis of a land map obtained from satellite observation (actually, the oldest application of this type) or to understand if the cell you are looking at is cancerous or perfectly healthy. For all these reasons, HSI represents one of the most exciting methodologies of the new millennium.

Hyperspectral Imaging And Their Applications In The Nondestructive Quality Assessment Of Fruits And Vegetables
Author: Xiaona Li
Publisher:
Release Date: 2018
Pages:
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Over the past decade, hyperspectral imaging has been rapidly developing and widely used as an emerging scientific tool in nondestructive fruit and vegetable quality assessment. Hyperspectral imaging technique integrates both the imaging and spectroscopic techniques into one system, and it can acquire a set of monochromatic images at almost continuous hundreds of thousands of wavelengths. Many researches based on spatial image and/or spectral image processing and analysis have been published proposing the use of hyperspectral imaging technique in the field of quality assessment of fruits and vegetables. This chapter presents a detailed overview of the introduction, latest developments and applications of hyperspectral imaging in the nondestructive assessment of fruits and vegetables. Additionally, the principal components, basic theories, and corresponding processing and analytical methods are also reported in this chapter.

Hyperspectral Imaging Technology In Food And Agriculture
Author: Bosoon Park
Publisher: Springer
Release Date: 2015-09-29
Pages: 403
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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 recent years, hyperspectral imaging has attracted much research and development attention, as a result rapid scientific and technological advances have increasingly taken place in food and agriculture, especially on safety and quality inspection, classification and evaluation of a wide range of food products, illustrating the great advantages of using the technology for objective, rapid, non-destructive and automated safety inspection as well as quality control. Therefore, as the first reference book in the area, Hyperspectral Imaging Technology in Food and Agriculture focuses on these recent advances. The book is divided into three parts, which begins with an outline of the fundamentals of the technology, followed by full covering of the application in the most researched areas of meats, fruits, vegetables, grains and other foods, which mostly covers food safety and quality as well as remote sensing applicable for crop production. Hyperspectral Imaging Technology in Food and Agriculture is written by international peers who have both academic and professional credentials, with each chapter addressing in detail one aspect of the relevant technology, thus highlighting the truly international nature of the work. Therefore the book should provide the engineer and technologist working in research, development, and operations in the food and agricultural industry with critical, comprehensive and readily accessible information on the art and science of hyperspectral imaging technology. It should also serve as an essential reference source to undergraduate and postgraduate students and researchers in universities and research institutions.

Hyperspectral Imaging Analysis And Applications For Food Quality
Author: N.C. Basantia
Publisher: CRC Press
Release Date: 2018-11-16
Pages: 284
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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 making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes. Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.

Application Of Hyperspectral Imaging In Forensic Science
Author: Siying Wang
Publisher:
Release Date: 2018
Pages: 372
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

The aim of this research was to study and compare two different configurations of hyperspectral imaging (HSI) systems, an area-scan hyperspectral imaging system and a line-scan hyperspectral imaging system, and investigate their applicability in forensic science. Compared to the area-scan HSI system, the line-scan system required a stable and continuous movement of the sample and suffered from more noise due to its higher spectral resolution and lower light throughput. However, the line-scan HSI system was extremely useful for resolving chromophores and fluorophores which have spectral features that had small widths or were close together, whereas the lower spectral resolution of the area-scan HSI system resulting in partial or complete loss of these spectral features. The line-scan HSI system also performed better for an example of structural colour, porous silicon, which has closely-spaced interference fringes in its spectral dimension. The slight change in polarity of fingermarks caused by ozone exposure was also studied using HSI systems. Charged fingermarks deposited on glass were either exposed to ozone or left unexposed, and then all fingermarks were stained with the solvatochromic dye Nile Red and then imaged. The area-scan HSI system was better for this fingermark imaging and in most cases, the slight shift in wavelength of the Nile Red fluorescence could be detected by this system. Different fluorescence behaviour was found for fingermarks that had been stained with Nile Red suspended in the fluorous solvent HFE-7100 compared to with methanolic Nile Red, and these differences were analysed using principal component analysis (PCA). The aging of fingermarks deposited on polyethylene was also examined using HSI, and this study shows that fingermarks tend to penetrate into the polyethylene over a period of a few days. The use of the area-scan HSI system for iodine detection on a polyethylene substrate was studied. Since iodine has a broad absorption in the blue and near-UV, the HSI system did not give improved performance compared to traditional imaging. A new application of HSI for the discrimination of polypropylene lids was then investigated. Nine polypropylene lids were imaged using the area-scan HSI system with a crossed polarised filter. The image cube acquired with this system were processed with a fast Fourier transform to determine the optical retardation over the lids. Each polypropylene lid had a unique retardation map due to the slightly different thermochemical experience during the injection moulding process used in lid fabrication. This research has shown that HSI is a powerful tool in the detection of chromophores, fluorophores, and structural colour in forensic science. HSI allows investigation of both spatial properties and spectral characteristics, especially when HSI is combined with principal component analysis or multivariate curve resolution.

Hyperspectral Imaging For Food Quality Analysis And Control
Author: Da-Wen Sun
Publisher: Elsevier
Release Date: 2010-06-29
Pages: 496
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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 practically applied for food quality assessment, including information on the equipment available and selection of the most appropriate of those instruments. Additionally, real-world food-industry-based examples are included, giving the reader important insights into the actual application of the science in evaluating food products. Presentation of principles and instruments provides core understanding of how this science performs, as well as guideline on selecting the most appropriate equipment for implementation Includes real-world, practical application to demonstrate the viability and challenges of working with this technology Provides necessary information for making correct determination on use of hyperspectral imaging

Hyperspectral Imaging In Agriculture  Food And Environment
Author: Alejandro Isabel Luna Maldonado
Publisher: BoD – Books on Demand
Release Date: 2018-08-01
Pages: 184
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

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 process hyperspectral image, and soil contamination mapping with hyperspectral imagery. This book is a general reference work for students, professional engineers, and readers with interest in the subject.

Advances In Hyperspectral Imaging Research
Author: Jena Grant
Publisher:
Release Date: 2014-01-01
Pages: 97
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Hyperspectral imaging (HSI), known also as chemical or spectroscopic imaging, is an emerging platform technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Although hyperspectral imaging was originally developed for remote sensing, it recently has gained wide recognition as a non-destructive and fast quality and safety analysis and assessment method for a wide range of food products. This book discusses hyperspectral imaging data processes and its application in food products, as well as the use of HSI for detecting changes in retinal vessel blood oxygen saturation; the performance evaluation of CCSDS lossless compression standard for multi/HSI; and multidimensional approach of infrared imaging spectra and morphology of oral squamous cell carcinoma.

Quantitative Hyperspectral Imaging Pipeline To Recover Surface Images From CRISM Radiance Data
Author: Linyun He
Publisher:
Release Date: 2019
Pages: 130
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Hyperspectral data are important for remote applications such as mineralogy, geology, agriculture and surveillance sensing. A general pipeline converting measured hyperspectral radiance to the surface reflectance image can provide planetary scientists with clean, robust and repeatable products to work on.In this dissertation, the surface single scattering albedos (SSAs), the ratios of scattering eciency to scattering plus absorption eciences of a single particle, are selected to describe the reflectance. Moreover, the IOF, the ratio of measured spectral radiance (in the unit of watts per squared-meter and micrometer) to the solar spectral radiance (in the unit of watts per squared-meter and micrometer) at the observed time, is used to indicate the measurements.This pipeline includes two main parts: retrieving SSAs from IOF and reconstructing the SSA images from the SSA cube. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on the Mars Reconnaissance Orbiter (MRO) helps scientists identify locations on Mars that may have exhibit hydrated mineral phases. This dissertation mainly focuses on developing the pipeline for CRISM data. One should notice that pipelines for other hyperspectral spectrometers can also be developed based on almost the same idea. Retrieving surface kinetic temperatures and SSA values from IOF data is challenging because the problem is under-determined and ill-posed, including modulating effects of atmospheric aerosols and gases, and surface scattering and emission properties. We introduce a general framework called STANN (Separating Temperature and Albedo using Neural Networks) to solve this kind of problem. STANN takes the hyperspectral IOF cube as inputs and outputs the retrieved temperature mapping and the corresponding SSA cube. Our STANN is derived using the Discrete Ordinates Radiative Transfer function to describe the forward model from SSA and temperature to IOF. In the STANN, we have a generator to generate more training samples based on limited library spectra and a neural network to approximate the inverse function based on enough generated training samples. This framework has been implemented for the Compact Imaging Spectrometer for Mars in a detailed manner. SSA can be computed from IOF directly by modeling the thermal and solar reflectance together, based on retrieved temperatures. Because accurate retrieved temperature directly leads to accurate SSA, we compare the accuracy of retrieved temperatures from STANN.The retrieved temperature has only 4 K error by one point validation (242 K) using the Curiosity Rover's thermal radiometer data. Our STANN temperature map is compared with a temperature map generated independently from a theoretical thermal model. The theoretical thermal model describes the relationship between Lambert albedo at the wavelength 1.0 [mu]m, thermal inertia and the surface temperature. However, because the thermal inertia has pixel size larger than 100 m/pixel, the generated temperature also has the same pixel size. Our STANN temperature is projected into the same pixel size (100 m/pixel) by the classic projection method. The two temperature maps have consistent global patterns.Retrieved from an IOF cube, a noisy hyperspectral SSA cube needs to be denoised and reconstructed onto the Mars surface. We propose a new algorithm, hypothesis-based estimation with regularization (HyBER), to reconstruct and denoise hyperspectral image data without extra statistical assumptions. The hypothesis test selects the best statistical model approximating measurements based on the data only. Gaussian and Poisson distributions are common respectively for continuous and integer random variables, due to the law of large numbers. Hyperspectral IOF data result from converting discrete photon counting data to continuous electrical signals after calibration. Thus, so far, Gaussian and Poisson are candidate distributions for our hypothesis tests. A regularized maximum log-likelihood estimation method is derived based on the selected model. A spatially dependent weighting on the regularization penalty is presented, substantially eliminating row artifacts that are due to non-uniform sampling. A new spectral weighting penalty is introduced to suppress varying detector-related noise. HyBER generates reconstructions with sharpened images and spectra in which the noise is suppressed, whereas fine-scale mineral absorptions are preserved. The performance is quantitatively analyzed for simulations with relative error 0.002%, which is better than the traditional non-statistical methods (baselines) and statistical methods with improper assumptions. When applied to the Mars Reconnaissance Orbiter's Compact Reconnaissance Imaging Spectrometer for Mars data, the spatial resolution and contrast are about 2 times better as compared to map projecting data without the use of HyBER. So far, part of our results has enabled planetary scientists to identify minerals and understand the forming history of Mars craters. Some of these findings are verified by the Opportunity Rover's measurements. In the future, results from this pipeline for CRISM are promising to play more and more critical roles in the planetary science.

Hyperspectral Imaging Remote Sensing
Author: Dimitris Manolakis
Publisher: Cambridge University Press
Release Date: 2016-10-31
Pages: 720
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Understand the seminal principles, current techniques, and tools of imaging spectroscopy with this self-contained introductory guide.

Short Wave Infrared  SWIR  Hyperspectral Imaging Technique For Examination Of Aflatoxin B1  AFB1  On Corn Kernels
Author:
Publisher:
Release Date: 2015
Pages:
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Hyperspectral Imagery Warfighting Through A Different Set Of Eyes
Author:
Publisher: DIANE Publishing
Release Date:
Pages:
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Hyperspectral Imaging For Intelligence  Surveillance  And Reconnaissance
Author:
Publisher:
Release Date: 2001
Pages: 10
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This paper highlights SSC San Diego contributions to the research and development of hyperspectral technology. SSC San Diego developed the real-time, onboard hyperspectral data processor for automated cueing of high-resolution imagery as part of the Adaptive Spectral Reconnaissance Program (ASRP), which demonstrated a practical solution to broad area search by leveraging hyperspectral phenomenology. The authors explain how the DARPA ASRP successfully demonstrated the capability to detect military targets of interest in real time by using an airborne hyperspectral system to cue high-resolution images for ground analysis. SSC San Diego is now implementing the ASRP algorithm suite on parallel processors, using a portable, scalable architecture that will be remotely accessible. SSC San Diego performed the initial demonstrations that led to the Littoral Airborne Sensor Hyperspectral (LASH) program, which applies hyperspectral imaging to the problem of submarine detection in the littoral zone. These sensors can perform a wide range of ocean sensing tasks. Targets range from submarines and sea mines for military applications, to chlorophyll and sediment load in physical oceanographic applications, to schools of dolphins and whales in marine biology applications. Hyperspectral systems such as LASH are being developed that use spectral and spatial processing algorithms to discern objects and organisms below the sea surface. The performance of such systems depends on environmental and optical properties of the sea. An instrument suite, the Portable Profiling Oceanographic Instrument System (PorPOIS), was developed to ascertain and quantify these environmental and hydro-optic conditions. Under the In-house Laboratory Independent Research (ILIR) program, SSC San Diego has developed new and enhanced methods for hyperspectral analysis and exploitation.

Medical Imaging And Augmented Reality
Author: Takeyoshi Dohi
Publisher: Springer Science & Business Media
Release Date: 2008-07-16
Pages: 441
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This book constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008. The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation.

Mobile Hyperspectral Imaging For Structural Damage Detection
Author: Sameer Aryal
Publisher:
Release Date: 2020
Pages: 109
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Numerous optical-imaging and machine-vision based inspection methods are found that aim to replace visual and human-based inspection with an automated or a highly efficient procedure. However, these machine-vision systems have not been entirely endorsed by civil engineers towards deploying these techniques in practice, partially due to their poor performance in object detection when structural cracks coexist with other complex scenes. A mobile hyperspectral imaging system is developed in this work, which captures hundreds of spectral reflectance values at a pixel in the visible and near-infrared (VNIR) portion of the electromagnetic spectrum bands. To prove its potential in discriminating complex objects, a machine learning methodology is developed with classification models that are characterized by four different feature extraction processes. Experimental validation with quantitative measures proves that hyperspectral pixels, when used conjunctly with dimensionality reduction, possess outstanding potential in recognizing eight different structural surface objects including cracks for concrete and asphalt surfaces, and outperform the gray-values that characterize the texture/shape of the objects. The authors envision the advent of computational hyperspectral imaging for automating structural damage inspection, especially when dealing with complex structural scenes in practice.

Development Of An AOTF Based Hyperspectral Imager For Atmospheric Remote Sensing
Author: Emmanuel Dekemper
Publisher: Presses universitaires de Louvain
Release Date: 2014-11-07
Pages: 198
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

This work addresses important aspects in the development of a new spaceborne instrument called ALTIUS. The imaging capability is first applied to the inversion of atmospheric pressure profiles from the analysis of the apparent flattening of a setting...

Hyperspectral Imaging And Sounding Of The Environment  2007
Author:
Publisher:
Release Date: 2012
Pages:
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Use Of Hyperspectral Imaging For The Study Of Hemoglobin Oxygen Saturation In The Microcirculation
Author: Alfredo Lucas
Publisher:
Release Date: 2019
Pages: 104
ISBN:
Available Language: English, Spanish, And French
EBOOK SYNOPSIS:

Hyperspectral imaging is an imaging modality that combines imaging and spectroscopy in the same system. The ability to combine spectral and spatial information in the same modality allows for spectral analysis at every spatial location in a given image. This thesis will present a novel hyperspectral imaging approach for the study of the microcirculation in vivo. The approach involves the use of a spatial-scanning hyperspectral imaging technique, coupled with an efficient processing pipeline. Much of the literature involving the use of hyperspectral imaging for the study of the microcirculation in vivo has focused in very spatially limited approaches that involve the use of spectral-scanning hyperspectral imaging systems. With the spatial-scanning approach, a wider field of view, and superior spatial resolution is achieved, allowing for better averaging and higher statistical power in the results. Chapter 1 is a brief introduction. Chapter 2 presents a literature review of the different hyperspectral imaging modalities and their respective biomedical applications. A comprehensive review of the current state of the literature regarding the use of hyperspectral imaging for the study of the microcirculation in vivo is also included. Chapter 3 presents a work currently submitted for publication in which a spatial-scanning hyperspectral imaging approach is used to study hypoxia dynamics in a hamster window chamber model. Chapter 4 presents a mathematical modeling of post-hypoxic hemoglobin reoxygenation dynamics in a mouse window chamber, measured by hyperspectral imaging. Finally, Chapter 5 presents the use of hyperspectral imaging for the monitoring of hemoglobin oxygenation dynamics during hemorrhagic shock onset, resuscitation and recovery.