- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Difference-based target detection using Mahalanobis distance and spectral angle
摘要： Two difference-based target detection methods are proposed in this work. In contrast to many target detectors which only calculate the distance between the testing pixel to the target spectrum, the proposed methods calculate the distance of the testing pixel to both of target and of background spectra. In other words, they utilize the difference between target and background computed distances. The first proposed method uses the Mahalanobis distance and benefits the valuable information contained in the statistics of targets and background. The second proposed method uses the kernel-based spectral angle mapper to benefit the advantages of spectral angle and kernel trick to separate targets from background, especially in non-linear cases. The experiments done on three real hyperspectral images indicate the high detection probability of the proposed methods compared to several target detectors.
关键词： hyperspectral imaging,Mahalanobis distance,target detection,spectral angle
更新于2025-09-09 09:28:46
-
[IEEE 2018 IEEE International Symposium on Technologies for Homeland Security (HST) - Woburn, MA, USA (2018.10.23-2018.10.24)] 2018 IEEE International Symposium on Technologies for Homeland Security (HST) - Three-Dimensional Radiative Transfer for Hyperspectral Imaging Classification and Detection
摘要： Hyperspectral image exploitation algorithms typically require inputs of re?ectance spectra, which must be retrieved from the observed radiance spectra. This retrieval process is very challenging under the complex illumination conditions typical of urban settings due the in?uence of three-dimensional structure in the form of shadows and re?ections, which must be taken into account by the algorithms. In order to advance the state of the art on this problem, MIT Lincoln Laboratory recently conducted an airborne data collection experiment in a light urban environment that included hyperspectral, laser radar, and pan-chromatic modalities. A comprehensive ground truth data set was collected and extensive efforts were directed at sensor characterization to enable the development of hyper-spectral exploitation algorithms. Additionally, the laboratory is developing an extremely compact but high performance imaging spectrometer that will be ideal for the data collections required by this new image processing paradigm.
关键词： Remote sensing,Hyperspectral imaging,Ladar imaging
更新于2025-09-04 15:30:14
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Onshore Hydrocarbon Remote Sensing
摘要： Hydrocarbon detection is important for both environment monitoring and hydrocarbon exploration. Hyperspectral imaging and derived spectral indices are used to detect hydrocarbons. With appropriate indices, light hydrocarbons on bare ground are detected. Heavier hydrocarbons are more difficult to detect. Plastic items are very well detected. Shadows and vegetation are generating some false alarms. Detection of hydrocarbon in urban environment, or on bare soils will be possible using spectral indices while detection of hydrocarbon in remote vegetated country areas will be difficult.
关键词： oil spill detection,Hydrocarbon index,hyperspectral imaging,multispectral imaging
更新于2025-09-04 15:30:14
-
[ACM Press the 3rd International Conference - Seoul, Republic of Korea (2018.08.22-2018.08.24)] Proceedings of the 3rd International Conference on Biomedical Signal and Image Processing - ICBIP '18 - Application of Hyperspectral Imaging for Surface Defects Detection of Jujube
摘要： Hyperspectral imaging system with the range of 450–990 nm was developed to obtain the reflection spectral of "Kaohsiung 11" jujube with surface defects. Principal component analysis (PCA) was used to reduce the spectral dimensionality of hyperspectral image data and determine the wavebands used by band ratio method for quick detection of jujube surface defects. Two-band ratio (Q550/680) images were successfully used to differentiate surfaces with defects such as decay, rusty, fungus infection and insect bites from the sound surface. Due to the fact that rusty surface of "Kaohsiung 11" has no effect on the quality of flavor and texture, a threshold value for slope of reflectance spectra between 700 nm and 710 nm was used to differentiate the rusty region from other defect regions. The glare due to specular reflection from smooth and waxy surface of jujube may lead to error when the differentiation of surfaces with defects and sound surfaces was performed. The findings of this study can be used as a basis for developing effective algorithm to identify different types of defects on jujube surface.
关键词： Fruit defects,Jujube,Principal component analysis,Hyperspectral imaging
更新于2025-09-04 15:30:14
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Fuzzy Fusion of Change Vector Analysis and Spectral Angle Mapper for Hyperspectral Change Detection
摘要： Change Vector Analysis (CVA) is one of the most widely used approaches for change detection in multispectral and hyperspectral images. Although, in CVA, the spectral change vector (CV) comprises the angle as well as the magnitude of the change, typically only the magnitude measure is used as change criterion. On the other hand, the spectral angle mapper (SAM) uses only the angle measure as criterion for change detection. It is envisaged that combining the angle and magnitude for change detection (i.e. combining SAM and magnitude CVA) can improve the change detection performance, yet only a limited number of approaches have been proposed in the literature so far. This paper presents a novel fuzzy inference combination strategy that combines the angle and magnitude distances, referred to as Fuzzy CVA (FuzCVA), and is shown that the proposed approach can provide improved change detection performance by effectively combining magnitude and angle measures.
关键词： Hyperspectral Imaging,change detection,spectral angle mapper,fuzzy inference,change vector analysis
更新于2025-09-04 15:30:14
-
[Studies in Computational Intelligence] Recent Advances in Computer Vision Volume 804 (Theories and Applications) || Hyperspectral Image: Fundamentals and Advances
摘要： Hyperspectral remote sensing has received considerable interest in recent years for a variety of industrial applications including urban mapping, precision agriculture, environmental monitoring, and military surveillance as well as computer vision applications. It can capture hyperspectral image (HSI) with a lager number of land-cover information. With the increasing industrial demand in using HSI, there is a must for more ef?cient and effective methods and data analysis techniques that can deal with the vast data volume of hyperspectral imagery. The main goal of this chapter is to provide the overview of fundamentals and advances in hyperspectral images. The hyperspectral image enhancement, denoising and restoration, classical classi?cation techniques and the most recently popular classi?cation algorithm are discussed with more details. Besides, the standard hyperspectral datasets used for the research purposes are covered in this chapter.
关键词： image enhancement,restoration,Hyperspectral imaging,classification,remote sensing,denoising,datasets
更新于2025-09-04 15:30:14
-
Development of a radiative transfer model for the determination of toxic gases by Fourier transform–infrared spectroscopy with a support vector machine algorithm
摘要： This report describes a radiative transfer model for Fourier transform-infrared (FT-IR) spectroscopy to create close-to-reality toxic gas spectra by reflecting the unique spectral responses of detectors and using the atmospheric radiative transfer code, MODTRAN. This system can be highly useful in overcoming the limitations for measuring toxic gases in open environments. The emulated gas spectra can be used to train support vector machine (SVM) for chemical gas detection. Its detection performance is evaluated with nerve agents (tabun, sarin, soman, and cyclosarin) and a simulant gas (sulfur hexafluoride) for indoor and outdoor experiments by using two off-the-shelf FT-IR gas detectors. The experimental results show that the proposed SVM algorithm successfully detected and classified targeted gases while reducing false negative and false positive detection rates.
关键词： support vector machine gas detection,Fourier transform infrared remote sensing,support vector machine,hyperspectral imaging,Fourier transform – infrared spectroscopy,stand-off detection
更新于2025-09-04 15:30:14
-
A Novel Near-infrared Hyperspectral Absorption/Scattering Imaging Method using Multiple Ground Plates for Evaluating Polymer Composites
摘要： This paper proposes a nondestructive method of evaluating polymer composites using near-infrared (NIR) diffuse reflection spectroscopy with multiple ground plates. Wavelength-dependent absorption and reduced scattering coefficients were acquired to evaluate the chemical structure and the concentration of the substances from absorption and to determine the size and the dispersity of filler in the polymer domain from scattering. NIR spectra of the sample were measured on multiple ground plates, namely, “ground-plate-dependent” diffuse reflection spectra. The effects of the external reflection on the ground-plate-dependent diffuse reflection spectra were subsequently removed. The internal reflection coefficient was calculated based on the difference between the diffuse reflectances of the neat resin and ground plates without prior information of the incident angle of light and the refractive index of sample. The external reflection coefficient was evaluated by the gap of diffuse reflectances between the sample and a white ground plate. After the corrections of reflections, the spectra were fitted by a physical model of light propagation based on the two-flex theory to acquire the absorption and the reduced scattering coefficients. The calculated absorption coefficients indicated a good linear relationship with particle concentration. The calculated reduced scattering coefficients agreed with the theoretical values by Mie scattering theory. It was demonstrated that the proposed method achieved to the simultaneous evaluation of particulate-filler concentrations and sizes in polymer composites.
关键词： Near-infrared,Hyperspectral imaging,Absorption,Scattering,Polymer composites
更新于2025-09-04 15:30:14
-
[American Society of Agricultural and Biological Engineers 2017 Spokane, Washington July 16 - July 19, 2017 - ()] 2017 Spokane, Washington July 16 - July 19, 2017 - <i>Variety classification of maize kernels using near infrared (NIR) hyperspectral imaging</i>
摘要： Variety classification of maize kernels was evaluated using near infrared (NIR) hyperspectral imaging in this work. Firstly, NIR hyperspectral images of kernels of four widely used maize varieties were acquired within effective spectral range of 1000-2500 nm. Spectral math was used to compensate for minor lighting differences, and band math combined with threshold method was used to remove the background from images. Minimum noise fraction (MNF) was adopted to reduce noise. Texture features (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation) as appearance character of each maize kernel were calculated and extracted to establish classification model combined with spectra data. Moving average smoothing and standard normal variate were applied on the raw spectra extracted from hyperspectral images. Four optimal wavelengths (1352.20 nm, 1615.50 nm, 1733.10 nm, and 2478.20 nm) were selected by competitive adaptive reweighted sampling (CARS) method. Partial least squares discriminant analysis (PLSDA) was employed to build varieties classification models, based on full wavelength data, the four wavelengths data, and combination of spectral and textural features at four wavelengths, respectively. Results demonstrated that PLSDA model based on combination of spectral and textural features had the best performance with accuracies of 0.89, 0.83 for calibration and prediction set, which indicated the hyperspectral imaging technique with combination of spectral and textural features had a potential of application for variety classification.
关键词： Variety classification,Maize kernel,NIR hyperspectral imaging,Partial least squares discriminant analysis (PLSDA),Competitive adaptive reweighted sampling (CARS) method
更新于2025-09-04 15:30:14
-
Data Fusion of Two Hyperspectral Imaging Systems with Complementary Spectral Sensing Ranges for Blueberry Bruising Detection
摘要： Currently, the detection of blueberry internal bruising focuses mostly on single hyperspectral imaging (HSI) systems. Attempts to fuse different HSI systems with complementary spectral ranges are still lacking. A push broom based HSI system and a liquid crystal tunable filter (LCTF) based HSI system with different sensing ranges and detectors were investigated to jointly detect blueberry internal bruising in the lab. The mean reflectance spectrum of each berry sample was extracted from the data obtained by two HSI systems respectively. The spectral data from the two spectroscopic techniques were analyzed separately using feature selection method, partial least squares-discriminant analysis (PLS-DA), and support vector machine (SVM), and then fused with three data fusion strategies at the data level, feature level, and decision level. The three data fusion strategies achieved better classification results than using each HSI system alone. The decision level fusion integrating classification results from the two instruments with selected relevant features achieved more promising results, suggesting that the two HSI systems with complementary spectral ranges, combined with feature selection and data fusion strategies, could be used synergistically to improve blueberry internal bruising detection. This study was the first step in demonstrating the feasibility of the fusion of two HSI systems with complementary spectral ranges for detecting blueberry bruising, which could lead to a multispectral imaging system with a few selected wavelengths and an appropriate detector for bruising detection on the packing line.
关键词： data fusion,blueberry,hyperspectral imaging,bruising
更新于2025-09-04 15:30:14