• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.341-369
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• 2005

Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of airborne, spaceborne, and field hyperspectral image sensors were surveyed from the available literatures and internet search. To understand the current status of hyperspectral remote sensing technology and research development, we collected several hundreds research papers from international journals (IEEE Transactions on Geoscience and Remote Sensing, International Journal of Remote Sensing, Remote Sensing of Environment and AVIRIS Workshop Proceedings), and categorized them by sensor types, data processing techniques, and applications. Although several hyperspectral sensors have been developing, AVIRIS has been a primary data source that the most hyperspectral remote sensing researches were relied on. Since hyperspectral data have very large data volume with many spectral bands, several data processing techniques that are particularly oriented to hyperspectral data have been developed. Although atmospheric correction, spectral mixture analysis, and spectral feature extraction are among those processing techniques, they are still in experimental stage and need further refinement until the fully operational adaptation. Geology and mineral exploration were major application in early stage of hyperspectral sensing because of the distinct spectral features of rock and minerals that could be easily observed with hyperspectral data. The applications of hyperspectral sensing have been expanding to vegetation, water resources, and military areas where the multispectral sensing was not very effective to extract necessary information.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.299-300
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• 2007

Along with the development of imaging sensors, hyperspectral imaging technology is growing rapidly and contributing to many fields of science nowadays. However, the bulky size and complex structure make it difficult to be processed. Focused on in this paper is the clustering utility, implemented in HYVEW, a program involving tools and functions to manipulate with hyperspectral images. The clustering process aims to partition the surface of the imaged area into subregions by grouping the spectra subject to the similarity of spectra.

• 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.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.403-412
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• 2016

Compact Reconnaissance Imaging Spectrometer for Mars(CRISM) is 489-band hyperspectral camera of Mars Reconnaissance Orbiter(MRO) that provided data used on many mineral researches over Martian surface. For the detection of minerals in planet, mineral index using a few spectral bands have been used. In this study, we applied Matched Filter and Adaptive Cosine Estimator(ACE) target detection algorithm on CRISM data over Gusev Crater: landing site of Spirit(Mars Exploration Rover A) to investigate its mineral distribution. As a result, olivine, pyroxene, magnetite, etc. is detected at Gusev Crater's Columbia Hills. These results are corresponding to the Spirit rover's field survey result. It is expected that hyperspectral target detection algorithms can be used as effective and easy to use method for the detection and mapping of surface minerals in planet.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.101-111
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• 2022

This study analyzed the relationship between water turbidity and its reflectance, as measured using hyperspectral imaging. First, samples of turbid water were generated in boxes. This was followed by drone-based hyperspectral imaging and analysis of the correlation between the samples' measured turbidity and hyperspectral reflectance. The nine boxes for turbidity measurement were made of black acrylic that absorbed all light turbidity was induced using soil collected near Changhacheon, which causes turbidity in Imha Lake. The results indicate that the reflectance of wavelengths in the near-infrared region followed a pattern of increase with increasing soil content for each box. Analysis of this correlation between the turbidity and average reflectance measured in each box yielded a very high R² value of 0.8702, indicating that reflectance is a suitable proxy for turbidity.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.06b
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• pp.262-269
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• 1998

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.136-136
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• 2022

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1049-1051
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• 2003

This study investigated the use of airborne image data to provide estimates of within -field variability in soil properties and crop growth as an alternative to extensive field data collection. Hyperspectral and multispectral images were acquired in 2000, 2001, and 2002 for central Missouri experimental fields. Data were converted to reflectance using chemically-treated reference tarps with known reflectance levels. Geometric distortion of the hyperspectral pushbroom sensor images was corrected with a rubber sheeting transformation. Statistical analyses were used to relate image data to field-measured soil properties and crop characteristics. Results showed that this approach has potential; however, it is important to address a number of implementation issues to insure quality data and accurate interpretations.

• 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.

• Journal of Biosystems Engineering
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• v.40 no.2
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• pp.124-136
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• 2015

Purpose: Grain quality is a general concept that covers many characteristics, ranging from physical to biochemical and physiochemical properties. Rice aging during storage is currently a challenge in the rice industry, and is a complicated process involving changes in all of the above properties. Spectroscopic techniques can be used to obtain information on the quality of rice samples in a non-destructive manner. Methods: The objective of this review was to highlight the factors that contribute to rice quality and aging, and to describe various spectroscopic modalities, particularly vibrational and hyperspectral imaging, for the assessment of rice quality. Results: Starch and protein are the main components of the rice endosperm, and are therefore key factors contributing to eating and cooking quality. While the overall starch, protein, and lipid content in the rice grain remains essentially unchanged during storage, structural changes do occur. These changes affect pasting and gel properties, and ultimately the flavor of cooked rice. In addition, grain quality is significantly affected by growing and environmental conditions, such as water availability, temperature, fertilizer application, and salinity stress. These properties can be evaluated using spectroscopic techniques, and rice samples can be discriminated by using multivariate statistical analysis methods. Conclusion: Hyperspectral imaging and vibrational spectroscopy techniques have good potential for determining rice quality properties in a non-invasive manner, i.e., not requiring the introduction of instruments into the rice grain.