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hyperspectral imaging

Félix Zapata, Fernando E Ortega-Ojeda, Carmen García-Ruiz
Crime scene investigation (CSI) requires the ultimate available technology for a rapid, non-destructive, and accurate detection of a wide variety of evidence including invisible stains of bodily fluids. Particularly crucial is the discrimination of semen in stained evidence from sexual abuse cases. This is because those evidence have high odds of containing the DNA from the aggressor. To this aim, we demonstrated the potential of near infrared hyperspectral imaging (NIR-HSI) to make visible stains of semen, vaginal fluid, and urine on fabrics, which lays the bases to face the challenging visualization and discrimination of semen within bodily fluids mixtures...
May 1, 2017: Talanta
Dustin M Graham
No abstract text is available yet for this article.
February 17, 2017: Lab Animal
A Miernik, S Hein, K Wilhelm, M Schoenthaler
Analysis of the composition of a urinary stone is one of the most important steps in the clinical management of patients with urolithiasis. Fourier transform infrared spectroscopy, X-ray diffractometry and petrographic microscopy are the techniques currently used. Novel technical developments in recent years - such as Raman spectroscopy and hyperspectral imaging - have resulted in new approaches to improve urinary stone analysis. In future, table-top portable systems may be used that allow stones to be rapidly examined directly after the operation...
February 16, 2017: Aktuelle Urologie
Iban Amenabar, Simon Poly, Monika Goikoetxea, Wiwat Nuansing, Peter Lasch, Rainer Hillenbrand
Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm(-1). To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information...
February 15, 2017: Nature Communications
Tingkui Mu, Shaun Pacheco, Zeyu Chen, Chunmin Zhang, Rongguang Liang
In this paper, the design and experimental demonstration of a snapshot linear-Stokes imaging spectropolarimeter (SLSIS) is presented. The SLSIS, which is based on division-of-focal-plane polarimetry with four parallel linear polarization channels and integral field spectroscopy with numerous slit dispersive paths, has no moving parts and provides video-rate Stokes-vector hyperspectral datacubes. It does not need any scanning in the spectral, spatial or polarization dimension and offers significant advantages of rapid reconstruction without heavy computation during post-processing...
February 13, 2017: Scientific Reports
Changyeun Mo, Giyoung Kim, Moon S Kim, Jongguk Lim, Hyunjeong Cho, Jinyoung Yang Barnaby, Byoung-Kwan Cho
BACKGROUND: Nondestructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed to detect worms on fresh-cut lettuce. The optimal wavebands for detecting the worms were investigated using the one-way ANOVA and correlation analyses. RESULTS: The worm detection imaging algorithms, RSI-I(492-626)/492 , provided a prediction accuracy of 99.0%. The fluorescence HSI techniques indicated that the spectral images with a pixel size of 1 × 1 mm had the best classification accuracy for worms...
February 11, 2017: Journal of the Science of Food and Agriculture
Lingxia Huang, Yibin Zhou, Liuwei Meng, Di Wu, Yong He
This study investigated the potential of using hyperspectral imaging technique in tandem with chemometrics for rapid and invasive predicting total anthocyanin content and antioxidant activity of mulberry fruit. Two calibration methods of partial least square regression and least-squares support vector machines and three wavelength selection algorithms of successive projections algorithm, uninformation variable elimination, and competitive adaptive reweighted sampling were applied. The best prediction models for the analysis of total anthocyanin content and antioxidant activity had Rval(2) of 0...
June 1, 2017: Food Chemistry
Leyuan Fang, Nanjun He, Hui Lin
In this paper, an effective CANDECOMP/PARAFAC tensor-based compression (CPTBC) approach is proposed for on-ground hyperspectral images (HSIs). By considering the observed HSI cube as a whole three-order tensor, the proposed CPTBC method utilizes the CANDECOMP/PARAFAC tensor decomposition to decompose the original HSI data into the sum of R rank-1 tensors, which can simultaneously exploit both the spatial and spectral information of HSIs. Specifically, compared with the original HSI data, the R rank-1 tensors have fewer non-zero entries...
February 1, 2017: Journal of the Optical Society of America. A, Optics, Image Science, and Vision
Shaiju S Nazeer, Rarinthorn Samrid, David Perez-Guaita, Parichat Prachaney, Kowit Chaisiwamongkol, Poungrat Pakdeechote, Ponlatham Chaiyarit, Bayden R Wood
Fourier transform infrared spectroscopy (FTIR) imaging has been applied to investigate biochemical differences between salivary glands from control and hypertensive rats. Male Sprague-Dawley rats were divided into two groups including a control group and another hypertension group that were treated orally, with N-nitro-l-arginine methyl ester (l-NAME) via drinking water for 3 weeks to develop hypertension. In the control group, rats were treated with only drinking water for 3 weeks. The formalin-fixed paraffin embedded tissue specimens from submandibular and sublingual glands were analysed with a FTIR focal plane array imaging spectrometer and multi-composite images of all tissue sections were analysed simultaneously using Unsupervised Hierarchical Cluster Analysis (UHCA) and the extracted spectra were further analysed using Partial Least Squares Discriminant Analysis (PLS-DA)...
February 3, 2017: Analyst
James C K Dillon, Leonardo Bezerra, María Del Pilar Sosa Peña, Nicole M Neu-Baker, Sara A Brenner
Hyperspectral imaging (HSI) and mapping are increasingly used for visualization and identification of nanoparticles (NPs) in a variety of matrices, including aqueous suspensions and biological samples. Reference spectral libraries (RSLs) contain hyperspectral data collected from materials of known composition and are used to detect the known materials in experimental samples through a one-to-one pixel "mapping" process. In some HSI studies, RSLs created from raw NPs were used to map NPs in experimental samples in a different matrix; for example, RSLs created from NPs in suspension to map NPs in biological tissue...
January 31, 2017: Microscopy Research and Technique
Emilio Catelli, Lise Lyngsnes Randeberg, Bjørn Kåre Alsberg, Kidane Fanta Gebremariam, Silvano Bracci
Hyperspectral imaging (HSI) is a fast non-invasive imaging technology recently applied in the field of art conservation. With the help of chemometrics, important information about the spectral properties and spatial distribution of pigments can be extracted from HSI data. With the intent of expanding the applications of chemometrics to the interpretation of hyperspectral images of historical documents, and, at the same time, to study the colorants and their spatial distribution on ancient illuminated manuscripts, an explorative chemometric approach is here presented...
January 7, 2017: Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
Feifei Tao, Michael Ngadi
Conventional methods for determining fat content and fatty acids (FAs) composition are generally based on the solvent extraction and gas chromatography techniques, respectively, which are time-consuming, laborious, destructive to samples and require use of hazard solvents. These disadvantages make them impossible for large-scale detection or being applied to the production line of meat factories. In this context, the great necessity of developing rapid and non-destructive techniques for fat and FAs analyses has been highlighted...
January 24, 2017: Critical Reviews in Food Science and Nutrition
Maogui Wei, Paul Geladi, Shaojun Xiong
Commercial mushroom growth on substrate material produces a heterogeneous waste that can be used for bioenergy purposes. Hyperspectral imaging in the near-infrared (NHI) was used to experimentally study a number of spent mushroom substrate (SMS) packed samples under different conditions (wet vs. dry, open vs. plastic covering, and round or cuboid) and to explore the possibilities of direct characterization of the fresh substrate within a plastic bag. Principal components analysis (PCA) was used to remove the background of images, explore the important studied factors, and identify SMS and mycelia (Myc) based on the pixel clusters within the score plot...
January 23, 2017: Analytical and Bioanalytical Chemistry
Abraham Hirshberg, Irit Allon, Ilya Novikov, Rinat Ankri, Ariel Ashkenazy, Dror Fixler
Nanoparticle-based contrast agents have been used as an imaging tool for selectively detecting cancerous processes. We aimed to evaluate the detection sensitivity of reflection measurements of gold nanorods (GNRs) bio-conjugated to anti-epidermal growth factor receptor (GNRs-EGFR) monoclonal antibodies in discriminating benign from premalignant and malignant human oral lesions. Tissue sections incubated with GNRs-EGFR and the reflectance spectrum was measured using hyperspectral microscopy. Reflectance intensity increased with the progression of the disease, lowest in the control group and increasing as the dysplastic changes increase (p<0...
January 20, 2017: Nanomedicine: Nanotechnology, Biology, and Medicine
Reza Arablouei, Frank de Hoog
Natural images tend to mostly consist of smooth regions with individual pixels having highly correlated spectra. This information can be exploited to recover hyperspectral images of natural scenes from their incomplete and noisy measurements. To perform the recovery while taking full advantage of the prior knowledge, we formulate a composite cost function containing a square-error data-fitting term and two distinct regularization terms pertaining to spatial and spectral domains. The regularization for the spatial domain is the sum of total-variation of the image frames corresponding to all spectral bands...
September 27, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Qi Wang, Jianzhe Lin, Yuan Yuan
Saliency detection has been a hot topic in recent years, and many efforts have been devoted in this area. Unfortunately, the results of saliency detection can hardly be utilized in general applications. The primary reason, we think, is unspecific definition of salient objects, which makes that the previously published methods cannot extend to practical applications. To solve this problem, we claim that saliency should be defined in a context and the salient band selection in hyperspectral image (HSI) is introduced as an example...
March 18, 2016: IEEE Transactions on Neural Networks and Learning Systems
Shuo Yang, Zhenwei Shi
For the hyperspectral target detection, the neighbors of a target pixel are very likely to be target pixels, and those of a background pixel are very likely to be background pixels. In order to utilize this spatial homogeneity or smoothness, based on total variation (TV), we propose a novel supervised target detection algorithm which uses a single target spectrum as the prior knowledge. TV can make the image smooth, and has been widely used in image denoising and restoration. The proposed algorithm uses TV to keep the spatial homogeneity or smoothness of the detection output...
March 22, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Weisheng Dong, Fazuo Fu, Guangming Shi, Xun Cao, Jinjian Wu, Guangyu Li, Xin Li
Hyperspectral imaging has many applications from agriculture and astronomy to surveillance and mineralogy. However, it is often challenging to obtain High-resolution (HR) hyperspectral images using existing hyperspectral imaging techniques due to various hardware limitations. In this paper, we propose a new Hyperspectral image super-resolution method from a low-resolution (LR) image and a HR reference image of the same scene. The estimation of the HR hyperspectral image is formulated as a joint estimation of the hyperspectral dictionary and the sparse codes based on the prior knowledge of the spatialspectral sparsity of the hyperspectral image...
March 22, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Lizhi Wang, Zhiwei Xiong, Guangming Shi, Feng Wu, Wenjun Zeng
Leveraging the compressive sensing (CS) theory, coded aperture snapshot spectral imaging (CASSI) provides an efficient solution to recover 3D hyperspectral data from a 2D measurement. The dual-camera design of CASSI, by adding an uncoded panchromatic measurement, enhances the reconstruction fidelity while maintaining the snapshot advantage. In this paper, we propose an adaptive nonlocal sparse representation (ANSR) model to boost the performance of dualcamera compressive hyperspectral imaging (DCCHI). Specifically, the CS reconstruction problem is formulated as a 3D cube based sparse representation to make full use of the nonlocal similarity in both the spatial and spectral domains...
October 25, 2016: IEEE Transactions on Pattern Analysis and Machine Intelligence
Lefei Zhang, Qian Zhang, Bo Du, Xin Huang, Yuan Yan Tang, Dacheng Tao
In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier...
September 12, 2016: IEEE Transactions on Cybernetics
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