• Title, Summary, Keyword: Multispectral sensors

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Image Fusion Methods for Multispectral and Panchromatic Images of Pleiades and KOMPSAT 3 Satellites

  • Kim, Yeji;Choi, Jaewan;Kim, Yongil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.5
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    • pp.413-422
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    • 2018
  • Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

Automatic Cross-calibration of Multispectral Imagery with Airborne Hyperspectral Imagery Using Spectral Mixture Analysis

  • Yeji, Kim;Jaewan, Choi;Anjin, Chang;Yongil, Kim
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.3
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    • pp.211-218
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    • 2015
  • The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

Performance Evaluation of Pansharpening Algorithms for WorldView-3 Satellite Imagery

  • Kim, Gu Hyeok;Park, Nyung Hee;Choi, Seok Keun;Choi, Jae Wan
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.4
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    • pp.413-423
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    • 2016
  • Worldview-3 satellite sensor provides panchromatic image with high-spatial resolution and 8-band multispectral images. Therefore, an image-sharpening technique, which sharpens the spatial resolution of multispectral images by using high-spatial resolution panchromatic images, is essential for various applications of Worldview-3 images based on image interpretation and processing. The existing pansharpening algorithms tend to tradeoff between spectral distortion and spatial enhancement. In this study, we applied six pansharpening algorithms to Worldview-3 satellite imagery and assessed the quality of pansharpened images qualitatively and quantitatively. We also analyzed the effects of time lag for each multispectral band during the pansharpening process. Quantitative assessment of pansharpened images was performed by comparing ERGAS (Erreur Relative Globale Adimensionnelle de Synthèse), SAM (Spectral Angle Mapper), Q-index and sCC (spatial Correlation Coefficient) based on real data set. In experiment, quantitative results obtained by MRA (Multi-Resolution Analysis)-based algorithm were better than those by the CS (Component Substitution)-based algorithm. Nevertheless, qualitative quality of spectral information was similar to each other. In addition, images obtained by the CS-based algorithm and by division of two multispectral sensors were shaper in terms of spatial quality than those obtained by the other pansharpening algorithm. Therefore, there is a need to determine a pansharpening method for Worldview-3 images for application to remote sensing data, such as spectral and spatial information-based applications.

Calculation of correction coefficients for the RedEdge-MX multispectral camera through intercalibration with a hyperspectral sensor (초분광센서와의 상호교정을 통한 RedEdge-MX 다분광 카메라의 보정계수 산출)

  • Baek, Seungil;Koh, Sooyoon;Kim, Wonkook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.6
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    • pp.707-716
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    • 2020
  • Spectroradiometers have recently been drawing great attention in earth observing communities for its capability for obtaining target's quantitative properties. In particular, light-weighted multispectral cameras are gaining popularity in many field domains, as being utilized on UAV's. Despite the importance of the radiometric accuracy, studies are scarce on the performance of the inexpensive multispectral camera sensors that have various applications in agricultural, vegetation, and water quality analysis. This study conducted assessment of radiometric accuracy for MicaSense RedEdge-MX multispectral camera, by comparing the radiometric data with an independent hyperspectral sensor having NIST-traceable calibration quality. The comaprison showed that radiance from RedEdge-MX is lower than that of TriOS RAMSES by 5 to 16% depending on the bands, and the irradiance from RedEdge-MX is also lower than RAMSES by 1~20%. The correction coefficients for RedEdge-MX alculated through the 1-st and the 3-rd order regression analysis were presented as a result of the study.

Evaluation of Block-based Sharpening Algorithms for Fusion of Hyperion and ALI Imagery (Hyperion과 ALI 영상의 융합을 위한 블록 기반의 융합기법 평가)

  • Kim, Yeji;Choi, Jaewan
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.1
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    • pp.63-70
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    • 2015
  • An Image fusion, or Pansharpening is a methodology of increasing the spatial resolution of image with low-spatial resolution using high-spatial resolution images. In this paper, we have performed an image fusion of hyperspectral imagery by using panchromatic image with high-spatial resolution, multispectral and hyperspectral images with low-spatial resolution, which had been acquired by ALI and Hyperion of EO-1 satellite sensors. The study has been mainly focused on evaluating performance of fusion process following to the image fusion methodology of the block association, which had applied to ALI and Hyperion dataset by considering spectral characteristics between multispectral and hyperspectral images. The results from experiments have been identified that the proposed algorithm efficiently improved the spatial resolution and minimized spectral distortion comparing with results from a fusion of the only panchromatic and hyperspectral images and the existing block-based fusion method. Through the study in a proposed algorithm, we could concluded in that those applications of airborne hyperspectral sensors and various hyperspectral satellite sensors will be launched at future by enlarge its usages.

Co-registration Between PAN and MS Bands Using Sensor Modeling and Image Matching (센서모델링과 영상매칭을 통한 PAN과 MS 밴드간 상호좌표등록)

  • Lee, Chang No;Oh, Jae Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.1
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    • pp.13-21
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    • 2021
  • High-resolution satellites such as Kompsat-3 and CAS-500 include optical cameras of MS (Multispectral) and PAN (Panchromatic) CCD (Charge Coupled Device) sensors installed with certain offsets. The offsets between the CCD sensors produce geometric discrepancy between MS and PAN images because a ground target is imaged at slightly different times for MS and PAN sensors. For precise pan-sharpening process, we propose a co-registration process consisting the physical sensor modeling and image matching. The physical sensor model enables the initial co-registration and the image matching is carried out for further refinement. An experiment with Kompsat-3 images produced RMSE (Root Mean Square Error) 0.2pixels level of geometric discrepancy between MS and PAN images.

Detection Method of River Floating Debris Using Unmanned Aerial Vehicle and Multispectral Sensors (무인항공기 및 다중분광센서를 이용한 하천부유쓰레기 탐지 기법 연구)

  • Kim, Heung-Min;Yoon, HongJoo;Jang, SeonWoong;Chung, YongHyun
    • Korean Journal of Remote Sensing
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    • v.33 no.5_1
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    • pp.537-546
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    • 2017
  • This study aims to develop the floating debris detection algorithm using a Unmanned Aerial Vehicle (UAV) and multispectral sensors. In addition, the occurrence range of floating debris was estimated by applying the algorithm. An aerial photograph using an unmanned aerial vehicle was used to generate an orthoimage that can calculate the area. A spectrum survey of water, plants litter, polystyrene foam etc. was conducted. After obtaining spectroscopic characteristics of floating debris and water, the River Floating Debris (RFD) index was calculated. And we detected the floating debris through band combination of sensor using RFD. As a result of the RFD application, accumulation zone of floating debris was confirmed at three sites in the orthoimage. It was estimated that a lot of floating debris was accumulated at 0.82 ha ($8,200m^2$), which is corresponding to 3.6% including the accumulation zone.

Analysis of UAV-based Multispectral Reflectance Variability for Agriculture Monitoring (농업관측을 위한 다중분광 무인기 반사율 변동성 분석)

  • Ahn, Ho-yong;Na, Sang-il;Park, Chan-won;Hong, Suk-young;So, Kyu-ho;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1379-1391
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    • 2020
  • UAV in the agricultural application are capable of collecting ultra-high resolution image. It is possible to obtain timeliness images for phenological phases of the crop. However, the UAV uses a variety of sensors and multi-temporal images according to the environment. Therefore, it is essential to use normalized image data for time series image application for crop monitoring. This study analyzed the variability of UAV reflectance and vegetation index according to Aviation Image Making Environment to utilize the UAV multispectral image for agricultural monitoring time series. The variability of the reflectance according to environmental factors such as altitude, direction, time, and cloud was very large, ranging from 8% to 11%, but the vegetation index variability was stable, ranging from 1% to 5%. This phenomenon is believed to have various causes such as the characteristics of the UAV multispectral sensor and the normalization of the post-processing program. In order to utilize the time series of unmanned aerial vehicles, it is recommended to use the same ratio function as the vegetation index, and it is recommended to minimize the variability of time series images by setting the same time, altitude and direction as possible.

Absolute Radiometric Calibration for KOMPSAT-3 AEISS and Cross Calibration Using Landsat-8 OLI

  • Ahn, Hoyong;Shin, Dongyoon;Lee, Sungu;Choi, Chuluong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.4
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    • pp.291-302
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    • 2017
  • Radiometric calibration is a prerequisite to quantitative remote sensing, and its accuracy has a direct impact on the reliability and accuracy of the quantitative application of remotely sensed data. This paper presents absolute radiometric calibration of the KOMPSAT-3 (KOrea Multi Purpose SATellite-3) and cross calibration using the Landsat-8 OLI (Operational Land Imager). Absolute radiometric calibration was performed using a reflectance-based method. Correlations between TOA (Top Of Atmosphere) radiances and the spectral band responses of the KOMPSAT-3 sensors in Goheung, South Korea, were significant for multispectral bands. A cross calibration method based on the Landsat-8 OLI was also used to assess the two sensors using near simultaneous image pairs over the Libya-4 PICS (Pseudo Invariant Calibration Sites). The spectral profile of the target was obtained from EO-1 (Earth Observing-1) Hyperion data over the Libya-4 PICS to derive the SBAF (Spectral Band Adjustment Factor). The results revealed that the TOA radiance of the KOMPSAT-3 agree with Landsat-8 within 5.14% for all bands after applying the SBAF. The radiometric coefficient presented here appears to be a good standard for maintaining the optical quality of the KOMPSAT-3.

Spectral Sensing for Plant Stress Assessment - A Review -

  • Kim, Y.;Reid, J.F.
    • Agricultural and Biosystems Engineering
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    • v.7 no.1
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    • pp.27-41
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    • 2006
  • Assessment of nitrogen and chlorophyll content from crop leaves can help growers adjust N fertilizer rates to meet the demands of the crop. Numerous researchers have presented their studies about spectral signature of plant leaves to characterize the plant features. However, interrelational review and summary were limited and a communication gap exists between the plant science and optical engineering. Understanding the mechanism of leaf interaction to electromagnetic radiation and factors affecting spectrophotometric measurements can enhance the foundation of optical remote sensing technologies. This paper provides extensive review of previous works in optical sensing and explains the basics of plant optics, spectral measurements for plant stress, factors that affect sensitivity to spectral analysis, and applications that deploy optical remote sensing technologies.

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