• Title/Summary/Keyword: 초분광 이미지

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Classification of Hyperspectral Image Pixel using Optimal Band Selection based on Discrete Range (이산 범위 기반 최적 밴드 추출을 이용한 초분광 이미지 픽셀 분류)

  • Chang, Duhyeuk;Jung, Byeonghyeon;Heo, Junyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.149-154
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    • 2021
  • Unlike or common images, Hyperspectral images were taken by continuous electromagnetic spectral into numerous bands according to wavelengths and are high-capacity high-resolution images. It has more information than ordinary images, so it is used to explore objects and materials. To reduce the amount of information in hyper-spectral images to be processed, band selection is utilized. Existing band selection techniques are heuristic techniques based on statistics, which take a long time and often lack generality and universality. To compensate for this, this paper utilizes quantization concept to draw representative bands through Discrete Range, we use them for band selection algorithm. Experimental results showed that the proposed technique performed much faster than conventional band selection methods, and that the performance accuracy was similar to that of the original even though the number of bands was reduced by one-seventh to one-tenth.

Accuracy Assessment and Classification of Surface Contaminants of Stone Cultural Heritages Using Hyperspectral Image - Focusing on Stone Buddhas in Four Directions at Gulbulsa Temple Site, Gyeongju - (초분광 영상을 활용한 석조문화재 표면오염물 분류 및 정확도 평가 - 경주 굴불사지 석조사면불상을 중심으로 -)

  • Ahn, Yu Bin;Yoo, Ji Hyun;Choie, Myoungju;Lee, Myeong Seong
    • Journal of Conservation Science
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    • v.36 no.2
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    • pp.73-81
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    • 2020
  • Considering the difficulties associated with the creation of deterioration maps for stone cultural heritages, quantitative determination of chemical and biological contaminants in them is still challenging. Hyperspectral image analysis has been proposed to overcome this drawback. In this study, hyperspectral imaging was performed on Stone Buddhas Temple in Four Directions at Gulbulsa Temple Site(Treasure 121), and several surface contaminants were observed. Based on the color and shape, these chemical and biological contaminants were classified into ten categories. Additionally, a method for establishing each class as a reference image was suggested. Simultaneously, with the help of Spectral Angle Mapper algorithm, two classification methods were used to classify the surface contaminants. Method A focused on the region of interest, while method B involved the application of the spectral library prepared from the image. Comparison of the classified images with the reference image revealed that the accuracies and kappa coefficients of methods A and B were 52.07% and 63.61%, and 0.43 and 0.55, respectively. Additionally, misclassified pixels were distributed in the same contamination series.

Field and remote acquisition of hyperspectral information for classification of riverside area materials (현장 및 원격 초분광 정보 계측을 통한 하천 수변공간 재료 구분)

  • Shin, Jaehyun;Seong, Hoje;Rhee, Dong Sop
    • Journal of Korea Water Resources Association
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    • v.54 no.12
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    • pp.1265-1274
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    • 2021
  • The analysis of hyperspectral characteristics of materials near the South Han River has been conducted using riverside area measurements by drone installed hyperspectral sensors. Each spectrum reflectance of the riverside materials were compared and analyzed which were consisted of grass, concrete, soil, etc. To verify the drone installed hyperspectral measurements, a ground spectrometer was deployed for field measurements and comparisons for the materials. The comparison results showed that the riverside materials had their unique hyperspectral band characteristics, and the field measurements were similar to the remote sensing data. For the classification of the riverside area, the K-means clustering method and SVM classification method were utilized. The supervised SVM method showed accurate classification of the riverside area than the unsupervised K-means method. Using classification and clustering methods, the inherent spectral characteristic for each material was found to classify the riverside materials of hyperspectral images from drones.

Application of Hyperspectral Imaging System to Analyze Vascular Alteration for Preclinical Models (전임상 혈관분석을 위한 초분광 이미징 시스템의 활용)

  • Choe, Se-Woon;Woo, Young Woon
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.4
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    • pp.69-76
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    • 2015
  • We present microscopy based hyperspectral imaging system that successively shows high spatial (micrometer) and temporal resolutions (milisecond), and acquired pseudocolor hemoglobin saturation map a result of various image processing techniques can provide additional information such as oxygen transport, abnormal vascularity and therapeutic effects besides structural and physiological measurements in various diseases. To increase understanding of vascular defects several optical methods of imaging for preclinical/clinical assessment have been developed so far. However, they have some limitations for outcoming resolution and user satisfaction level compared to its cost. A hyperspectral imaging system has shown a wide range of vascular characteristics associated with hypervascularity, aberrant angiogenesis or abnormal vascular remodeling in many diseases. This vascular characteristic is considered as a key component to diagnose and detect a type of disease as evidenced by them.

A study on the tumor induced microvasculature using hyperspectral imaging system (초분광 이미징 시스템을 이용한 암 혈관 분석에 대한 연구)

  • Choe, Se-woon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.622-624
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    • 2015
  • Tumor hypoxia caused by the unique characteristics of solid tumor sites such as lowered vascular density, irregular vasculature, longitudinal oxygen gradient, and unbalanced oxygen consumption has decreased therapeutic efficacy in several clinical trials such as radiation, chemotherapy, and surgery. Hence, tumor oxygenation studies at microvascular levels are important to provide better understanding of the complexity of microvasculature oxygen transport and exchange with tissue. However, polarographic microelectodes, was employed to measure $pO_2$ at the microvasculature level, but it is difficult to perform and does not provide significant spatial and temporal information of oxygen delivery. In this research, we introduce the hyperspectral imaging system able to provide a wide range of vascular characteristics by spatial maps on hemoglobin saturation information for better understanding of the relationship between blood oxygen delivery, hypervascularity, aberrant angiogenesis at microvasculature levels during tumor growth.

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Optimal Band Selection Techniques for Hyperspectral Image Pixel Classification using Pooling Operations & PSNR (초분광 이미지 픽셀 분류를 위한 풀링 연산과 PSNR을 이용한 최적 밴드 선택 기법)

  • Chang, Duhyeuk;Jung, Byeonghyeon;Heo, Junyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.141-147
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    • 2021
  • In this paper, in order to improve the utilization of hyperspectral large-capacity data feature information by reducing complex computations by dimension reduction of neural network inputs in embedded systems, the band selection algorithm is applied in each subset. Among feature extraction and feature selection techniques, the feature selection aim to improve the optimal number of bands suitable for datasets, regardless of wavelength range, and the time and performance, more than others algorithms. Through this experiment, although the time required was reduced by 1/3 to 1/9 times compared to the others band selection technique, meaningful results were improved by more than 4% in terms of performance through the K-neighbor classifier. Although it is difficult to utilize real-time hyperspectral data analysis now, it has confirmed the possibility of improvement.

Selection on Optimal Bands to EstimateYield of the Chinese Cabbage Using Drone-based Hyperspectral Image (드론 기반 초분광 영상을 이용한 배추 단수 추정의 최적밴드 선정)

  • Na, Sang-il;Park, Chan-won;So, Kyu-ho;Ahn, Ho-yong;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.35 no.3
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    • pp.375-387
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    • 2019
  • The use of drone-based hyperspectral image offers considerable advantages in high resolution remote sensing applications. The primary objective of this study was to select the optimal bands based on hyperspectral image for the estimation yield of the chinese cabbage. The hyperspectral narrow bands were acquired over 403.36 to 995.19 nm using a 3.97 nm wide, 150 bands, drone-based hyperspectral imaging sensor. Fresh weight data were obtained from 2,031 sample for each field survey. Normalized difference vegetation indices were computed using red, red-edge and near-infrared bands and their relationship with quantitative each fresh weights were established and compared. As a result, predominant proportion of fresh weights are best estimated using data from three narrow bands, in order of importance, centered around 697.29 nm (red band), 717.15 nm (red-edge band) and 808.51 nm (near-infrared band). The study determined three spectral bands that provide optimal chinese cabbage productivity in the visible and near-infrared portion of the spectrum.

Comparative analysis of water surface spectral characteristics based on hyperspectral images for chlorophyll-a estimation in Namyang estuarine reservoir and Baekje weir (남양호와 백제보의 Chlorophyll-a 산정을 위한 초분광 영상기반 수체분광특성 비교 분석)

  • Jang, Wonjin;Kim, Jinuk;Kim, Jinhwi;Nam, Guisook;Kang, Euetae;Park, Yongeun;Kim, Seongjoon
    • Journal of Korea Water Resources Association
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    • v.56 no.2
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    • pp.91-101
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    • 2023
  • In this study, we estimated the concentration of chlorophyll-a (Chl-a) using hyperspectral water surface reflectance in an inland weir (Baekjae weir) and estuarine reservoir (Namyang Reservoir) for monitoring the occurrence of algae in freshwater in South Korea. The hyperspectral reflectance was measured by aircraft in Baekjae Weir (BJW) from 2016 to 2017, and a drone in Namyang Reservoir (NYR) from 2020 to 2021. The 30 reflectance bands (BJW: 400-530, 620-680, 710-730, 760-790 nm, NYR: 400-430, 655-680, 740-800 nm) that were highly related to Chl-a concentration were selected using permutation importance. Artificial neural network based Chl-a estimation model was developed using the selected reflectance in both water bodies. And the performance of the model was evaluated with the coefficient of determination (R2), the root mean square error (RMSE), and the mean absolute error (MAE). The performance evaluation results of the Chl-a estimation model for each watershed was R2: 0.63, 0.82, RMSE: 9.67, 6.99, and MAE: 11.25, 8.48, respectively. The developed Chl-a model of this study may be used as foundation tool for the optimal management of freshwater algal blooms in the future.

A Study of the Characteristics of Painting Materials Used in Welcome Feast for the Pyeongan Governor: Focusing on Banquet at Yeongwangjeong Pavilion (평안감사향연도(平安監司饗宴圖)의 채색 재료 특성 연구 -연광정연회도(練光亭宴會圖)를 중심으로-)

  • Park, Jin Ho;Chang, Yeon Hee;Ko, Soo Rin
    • Conservation Science in Museum
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    • v.28
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    • pp.109-136
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    • 2022
  • This study analyzes the , one of the three panels of 《Welcoming Banquets for the Governor of Pyeong-an》, a documentary painting of the late Joseon Dynasty, with the aim to identify the coloring materials used in the painting. The painting was first imaged at each wavelength in order to minimize the potential problems in the process of analyzing specific parts. This study applied X-rays to identify ink, gold, and organic and inorganic pigments and used infrared rays to find ink and copper-based pigments. It also applied hyperspectral imaging to distinguish organic pigments from black, blue, and green materials. It also analyzed spots selected for each color to identify the following materials: white lead (white), ink/indigo (black), a combination of red lead and cinnabar (red), pink dye, purple dye, iron oxides (brown), orpiment/dye (yellow), malachite/malachite and yellow dye/indigo (green), azurite/white lead and indigo/indigo (blue), indigo and cochineal (violet), and gold leaf (gold). It is expected that more efficient analysis will be made possible by securing a sufficient library for each wavelength.

Band Selection Algorithm based on Expected Value for Pixel Classification (픽셀 분류를 위한 기댓값 기반 밴드 선택 알고리즘)

  • Chang, Duhyeuk;Jung, Byeonghyeon;Heo, Junyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.107-112
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    • 2022
  • In an embedded system such as a drone, it is difficult to store, transfer and analyze the entire hyper-spectral image to a server in real time because it takes a lot of power and time. Therefore, the hyper-spectral image data is transmitted to the server through dimension reduction or compression pre-processing. Feature selection method are used to send only the bands for analysis purpose, and these algorithms usually take a lot of processing time depending on the size of the image, even though the efficiency is high. In this paper, by improving the temporal disadvantage of the band selection algorithm, the time taken 24 hours was reduced to around 60-180 seconds based on the 40000*682 image resolution of 8GB data, and the use of 7.6GB RAM was significantly reduced to 2.3GB using 45 out of 150 bands. However, in terms of pixel classification performance, more than 98% of analysis results were derived similarly to the previous one.