• Title, Summary, Keyword: hyperspectral imaging technology

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Outdoor Applications of Hyperspectral Imaging Technology for Monitoring Agricultural Crops: A Review

  • Ahmed, Mohammad Raju;Yasmin, Jannat;Mo, Changyeun;Lee, Hoonsoo;Kim, Moon S.;Hong, Soon-Jung;Cho, Byoung-Kwan
    • Journal of Biosystems Engineering
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    • v.41 no.4
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    • pp.396-407
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    • 2016
  • Background: Although hyperspectral imaging was originally introduced for military, remote sensing, and astrophysics applications, the use of analytical hyperspectral imaging techniques has been expanded to include monitoring of agricultural crops and commodities due to the broad range and highly specific and sensitive spectral information that can be acquired. Combining hyperspectral imaging with remote sensing expands the range of targets that can be analyzed. Results: Hyperspectral imaging technology can rapidly provide data suitable for monitoring a wide range of plant conditions such as plant stress, nitrogen status, infections, maturity index, and weed discrimination very rapidly, and its use in remote sensing allows for fast spatial coverage. Conclusions: This paper reviews current research on and potential applications of hyperspectral imaging and remote sensing for outdoor field monitoring of agricultural crops. The instrumentation and the fundamental concepts and approaches of hyperspectral imaging and remote sensing for agriculture are presented, along with more recent developments in agricultural monitoring applications. Also discussed are the challenges and limitations of outdoor applications of hyperspectral imaging technology such as illumination conditions and variations due to leaf and plant orientation.

Optical System Design and Image Processing for Hyperspectral Imaging Systems (초분광 분해기의 광학계 설계 및 영상 처리)

  • Heo, A-Young;Choi, Seung-Won;Lee, Jae-Hoon;Kim, Tae-Hyeong;Park, Dong-Jo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.2
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    • pp.328-335
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    • 2010
  • A hyperspectral imaging spectrometer has shown significant advantages in performance over other existing ones for remote sensing applications. It can collect hundreds of narrow, adjacent spectral bands for each image, which provides a wealth of information on unique spectral characteristics of objects. We have developed a compact hyperspectral imaging system that successively shows high spatial and spectral resolutions and fast data processing performance. In this paper, we present an overview of the hyperspectral imaging system including the strucure of geometrical optics and several image processing schemes such as wavelength calibration and noise reduction for image data on Visible and Near-Infrared(VNIR) and Shortwave-Infrared(SWIR) band.

HYPERSPECTRAL IMAGING SPECTROMETER WITH A NOVEL ZOOMING FUNCTION

  • Choi Jin;Kim Tae Hyung;Kong Hong Jin;Lee Jong-Ung
    • Proceedings of the KSRS Conference
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    • pp.213-216
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    • 2005
  • A novel hyperspectral imaging spectrometer controlling spatial and spectral resolution individually has been proposed. This imaging spectrometer uses a zoom lens as a telescope and a focusing element. It can change the spatial resolution fixing the spectral resolution or the spectral resolution fixing the spatial resolution. Here, we report the concept of the hyperspectral imaging spectrometer with the novel zooming function and the optical design of a zoom lens as the focusing element. By using lens module and third-order aberration theory, we have presented the initial design of four-group zoom lens with external entrance pupil. And the optimized zoom lens with a focal length of 50 to 150 mm is obtained from the initial design by the optical design software. As a result, the designed zoom lens shows satisfactory performances in wavelength range of 450 to 900 nm as a focusing element in an imaging spectrometer. Furthermore, the collimator lens of the imaging spectrometer is designed through the third-order aberration correction by using an iterative process.

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Decomposition of Interference Hyperspectral Images Based on Split Bregman Iteration

  • Wen, Jia;Geng, Lei;Wang, Cailing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3338-3355
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    • 2018
  • Images acquired by Large Aperture Static Imaging Spectrometer (LASIS) exhibit obvious interference stripes, which are vertical and stationary due to the special imaging principle of interference hyperspectral image (IHI) data. As the special characteristics above will seriously affect the intrinsic structure and sparsity of IHI, decomposition of IHI has drawn considerable attentions of many scientists and lots of efforts have been made. Although some decomposition methods for interference hyperspectral data have been proposed to solve the above problem of interference stripes, too many times of iteration are necessary to get an optimal solution, which will severely affect the efficiency of application. A novel algorithm for decomposition of interference hyperspectral images based on split Bregman iteration is proposed in this paper, compared with other decomposition methods, numerical experiments have proved that the proposed method will be much more efficient and can reduce the times of iteration significantly.

Multi-class support vector machines for paint condition assessment on the Sydney Harbour Bridge using hyperspectral imaging

  • Huynh, Cong Phuoc;Mustapha, Samir;Runcie, Peter;Porikli, Fatih
    • Structural Monitoring and Maintenance
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    • v.2 no.3
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    • pp.181-197
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    • 2015
  • Assessing the condition of paint on civil structures is an important but challenging and costly task, in particular when it comes to large and complex structures. Current practices of visual inspection are labour-intensive and time-consuming to perform. In addition, this task usually relies on the experience and subjective judgment of individual inspectors. In this study, hyperspectral imaging and classification techniques are proposed as a method to objectively assess the state of the paint on a civil or other structure. The ultimate objective of the work is to develop a technology that can provide precise and automatic grading of paint condition and assessment of degradation due to age or environmental factors. Towards this goal, we acquired hyperspectral images of steel surfaces located at long (mid-range) and short distances on the Sydney Harbour Bridge with an Acousto-Optics Tunable filter (AOTF) hyperspectral camera (consisting of 21 bands in the visible spectrum). We trained a multi-class Support Vector Machines (SVM) classifier to automatically assess the grading of the paint from hyperspectral signatures. Our results demonstrate that the classifier generates highly accurate assessment of the paint condition in comparison to the judgement of human experts.

Discriminant analysis of grain flours for rice paper using fluorescence hyperspectral imaging system and chemometric methods

  • Seo, Youngwook;Lee, Ahyeong;Kim, Bal-Geum;Lim, Jongguk
    • Korean Journal of Agricultural Science
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    • v.47 no.3
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    • pp.633-644
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    • 2020
  • Rice paper is an element of Vietnamese cuisine that can be used to wrap vegetables and meat. Rice and starch are the main ingredients of rice paper and their mixing ratio is important for quality control. In a commercial factory, assessment of food safety and quantitative supply is a challenging issue. A rapid and non-destructive monitoring system is therefore necessary in commercial production systems to ensure the food safety of rice and starch flour for the rice paper wrap. In this study, fluorescence hyperspectral imaging technology was applied to classify grain flours. Using the 3D hyper cube of fluorescence hyperspectral imaging (fHSI, 420 - 730 nm), spectral and spatial data and chemometric methods were applied to detect and classify flours. Eight flours (rice: 4, starch: 4) were prepared and hyperspectral images were acquired in a 5 (L) × 5 (W) × 1.5 (H) cm container. Linear discriminant analysis (LDA), partial least square discriminant analysis (PLSDA), support vector machine (SVM), classification and regression tree (CART), and random forest (RF) with a few preprocessing methods (multivariate scatter correction [MSC], 1st and 2nd derivative and moving average) were applied to classify grain flours and the accuracy was compared using a confusion matrix (accuracy and kappa coefficient). LDA with moving average showed the highest accuracy at A = 0.9362 (K = 0.9270). 1D convolutional neural network (CNN) demonstrated a classification result of A = 0.94 and showed improved classification results between mimyeon flour (MF)1 and MF2 of 0.72 and 0.87, respectively. In this study, the potential of non-destructive detection and classification of grain flours using fHSI technology and machine learning methods was demonstrated.

Applicability of Hyperspectral Imaging Technology for the Check of Cadastre's Land Category (지목조사를 위한 초분광영상의 활용성 검토 연구)

  • Lee, InSu;Hyun, Chang-Uk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.32 no.spc4_2
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    • pp.421-430
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    • 2014
  • Aerial imagery, Satellite imaging and Hyperspectral imaging(HSI) are widely using at mapping those of agriculture, woodland, waters shoreline, and land cover, but are rarely applied at the Cadastre. There are many study cases on the overlay of aerial imagery and satellite imaging with Cadastral Map and the upgrade and registration of Cadastre' Land Category, however, reported as successful. Therefore, this study has been aimed to show the use of the Hyperspectral Imaging technology for Cadastre, especially for the land category. Also, the HSI sensor could function as a geospatial acquisition tool for error checks of the existed land categories, and as a helpful tool for acquiring the attributes and spatial data, such as the agriculture, soil, and vegetation, etc. This result indicates that HSI sensor can implement the Multipurpse Cadastre(MPC) by fusing with the cadastral information.

Recent Trends of Hyperspectral Imaging Technology (초분광 이미징 기술동향)

  • Lee, M.S.;Kim, K.S.;Min, G.;Son, D.H.;Kim, J.E.;Kim, S.C.
    • Electronics and Telecommunications Trends
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    • v.34 no.1
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    • pp.86-97
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    • 2019
  • Over the past 30 years, significant developments have been made in hyperspectral imaging (HSI) technologies that can provide end users with rich spectral, spatial, and temporal information. Owing to the advances in miniaturization, cost reduction, real-time processing, and analytical methods, HSI technologies have a wide range of applications from remote-sensing to healthcare, military, and the environment. In this study, we focus on the latest trends of HSI technologies, analytical methods, and their applications. In particular, improved machine learning techniques, such as deep learning, allows the full use of HSI technologies in classification, clustering, and spectral mixture algorithms. Finally, we describe the status of HSI technology development for skin diagnostics.

Non-destructive quality prediction of truss tomatoes using hyperspectral reflectance imagery (초분광 영상을 이용한 송이토마토의 비파괴 품질 예측)

  • Kim, Dae-Yong;Cho, Byoung-Kwan;Kim, Young-Sik
    • Korean Journal of Agricultural Science
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    • v.39 no.3
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    • pp.413-420
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    • 2012
  • Spectroscopic measurement method based on visible and near-infrared wavelengths was prominent technology for rapid and non-destructive evaluation of internal quality of fruits. Reflectance measurement was performed to evaluate firmness, soluble solid content, and acid content of truss tomatoes by hyperspectral reflectance imaging system. The Vis/NIR reflectance spectra was acquired from truss tomatoes sorted by 6 ripening stages. The multivariable analysis based on partial least square (PLS) was used to develop regression models with several preporcessing methods, such as smoothing, normalization, multiplicative scatter correction (MSC), and standard normal variate (SNV). The best model was selected in terms of coefficient of determination of calibration ($R_c^2$) and full cross validation ($R_{cv}^2$), and root mean standard error of calibration (RMSEC) and full cross validation (RMSECV). The results of selected models were 0.8976 ($R_p^2$), 6.0207 kgf (RMSEP) with gaussian filter of smoothing, 0.8379 ($R_p^2$), $0.2674^{\circ}Bx$ (RMSEP) with the mean of normalization, and 0.7779 ($R_p^2$), 0.1033% (RMSEP) with median filter of smoothing for firmness, soluble solid content (SSC), and acid content, respectively. Results show that Vis / NIR hyperspectral reflectance imaging technique has good potential for the measurement of internal quality of truss tomato.

A Mechanism Study of a HyperSpectral Image Sensor for Nadir and Slant Range Operation (직하방과 빗각 촬영 운용을 위한 초분광 영상센서 구동방식에 관한 연구)

  • Lee, Kyeongyeon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.4
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    • pp.484-491
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    • 2019
  • General Hyperspectral Image Sensor acquires an image of line form such as a thin rectangle shape because of using 1D array Push Broom or Whisk Broom scanning method. A special mechanism is required for a Hyperspectral Image Sensor to operate for nadir and slant range. To design the mechanism, the characteristics of the flight motion and the overlap rate between consecutive frames were analyzed. Also, system requirements were proposed through modeling and simulation.