• Title/Summary/Keyword: spectral image

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GENERATION OF FOREST FRACTION MAP WITH MODIS IMAGES USING ENDMEMBER EXTRACTED FROM HIGH RESOLUTION IMAGE

  • Kim, Tae-Geun;Lee, Kyu-Sung
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.468-470
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    • 2007
  • This paper is to present an approach for generating coarse resolution (MODIS data) fraction images of forested region in Korea peninsula using forest type area fraction derived from high resolution data (ASTER data) in regional forest area. A 15-m spatial resolution multi-spectral ASTER image was acquired under clear sky conditions on September 22, 2003 over the forested area near Seoul, Korea and was used to select each end-member that represent a pure reflectance of component of forest such as different forest, bare soil and water. The area fraction of selected each end-member and a 500-m spatial resolution MODIS reflectance product covering study area was applied to a linear mixture inversion model for calculating the fraction image of forest component across the South Korea. We found that the area fraction values of each end-member observed from high resolution image data could be used to separate forest cover in low resolution image data.

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Hyperspectral Image Analysis (하이퍼스펙트럴 영상 분석)

  • 김한열;김인택
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.11
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    • pp.634-643
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    • 2003
  • This paper presents a method for detecting skin tumors on chicken carcasses using hyperspectral images. It utilizes both fluorescence and reflectance image information in hyperspectral images. A detection system that is built on this concept can increase detection rate and reduce processing time, because the procedure for detection can be simplified. Chicken carcasses are examined first using band ratio FCM information of fluorescence image and it results in candidate regions for skin tumor. Next classifier selects the real tumor spots using PCA components information of reflectance image from the candidate regions. For the real world application, real-time processing is a key issue in implementation and the proposed method can accommodate the requirement by using a limited number of features to maintain the low computational complexity. Nevertheless, it shows favorable results and, in addition, uncovers meaningful spectral bands for detecting tumors using hyperspectral image. The method and findings can be employed in implementing customized chicken tumor detection systems.

Reconstruction of Buildings from Satellite Image and LIDAR Data

  • Guo, T.;Yasuoka, Y.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.519-521
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    • 2003
  • Within the paper an approach for the automatic extraction and reconstruction of buildings in urban built-up areas base on fusion of high-resolution satellite image and LIDAR data is presented. The presented data fusion scheme is essentially motivated by the fact that image and range data are quite complementary. Raised urban objects are first segmented from the terrain surface in the LIDAR data by making use of the spectral signature derived from satellite image, afterwards building potential regions are initially detected in a hierarchical scheme. A novel 3D building reconstruction model is also presented based on the assumption that most buildings can be approximately decomposed into polyhedral patches. With the constraints of presented building model, 3D edges are used to generate the hypothesis and follow the verification processes and a subsequent logical processing of the primitive geometric patches leads to 3D reconstruction of buildings with good details of shape. The approach is applied on the test sites and shows a good performance, an evaluation is described as well in the paper.

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An Adaptive Weighted Regression and Guided Filter Hybrid Method for Hyperspectral Pansharpening

  • Dong, Wenqian;Xiao, Song
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.327-346
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    • 2019
  • The goal of hyperspectral pansharpening is to combine a hyperspectral image (HSI) with a panchromatic image (PANI) derived from the same scene to obtain a single fused image. In this paper, a new hyperspectral pansharpening approach using adaptive weighted regression and guided filter is proposed. First, the intensity information (INT) of the HSI is obtained by the adaptive weighted regression algorithm. Especially, the optimization formula is solved to obtain the closed solution to reduce the calculation amount. Then, the proposed method proposes a new way to obtain the sufficient spatial information from the PANI and INT by guided filtering. Finally, the fused HSI is obtained by adding the extracted spatial information to the interpolated HSI. Experimental results demonstrate that the proposed approach achieves better property in preserving the spectral information as well as enhancing the spatial detail compared with other excellent approaches in visual interpretation and objective fusion metrics.

A Study on the Hyperspectral Image Classification with the Iterative Self-Organizing Unsupervised Spectral Angle Classification (반복최적화 무감독 분광각 분류 기법을 이용한 하이퍼스펙트럴 영상 분류에 관한 연구)

  • Jo Hyun-Gee;Kim Dae-Sung;Yu Ki-Yun;Kim Yong-Il
    • Korean Journal of Remote Sensing
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    • v.22 no.2
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    • pp.111-121
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    • 2006
  • The classification using spectral angle is a new approach based on the fact that the spectra of the same type of surface objects in RS data are approximately linearly scaled variations of one another due to atmospheric and topographic effects. There are many researches on the unsupervised classification using spectral angle recently. Nevertheless, there are only a few which consider the characteristics of Hyperspectral data. On this study, we propose the ISOMUSAC(Iterative Self-Organizing Modified Unsupervised Spectral Angle Classification) which can supplement the defects of previous unsupervised spectral angle classification. ISOMUSAC uses the Angle Division for the selection of seed points and calculates the center of clusters using spectral angle. In addition, ISOMUSAC perform the iterative merging and splitting clusters. As a result, the proposed algorithm can reduce the time of processing and generate better classification result than previous unsupervised classification algorithms by visual and quantitative analysis. For the comparison with previous unsupervised spectral angle classification by quantitative analysis, we propose Validity Index using spectral angle.

Damage Degree Valuation of Forest Using NDVI from Near Infrared CCD Camera and Spectral Radiometer in a Forest Fire Area (근적외 CCD카메라와 분광반사계의 식생지수를 이용한 산불 발생지역에서의 산림 피해도 평가)

  • Choi, Seung-Pil;Kim, Dong-Hee;Park, Jong-Sun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.23 no.4
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    • pp.367-374
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    • 2005
  • Recently, forest damage has occurred often and made big issues. Among them, the damage by forest fire is not only damage of itself but also being connected with secondary damage like a flood. This is the fact that a forest fire is caused rather artificially by people than nature. In this study, we try to investigate damage of a forest fire through spectral reflectance of a plant community surveyed using a near infrared CCD camera and a SPM (Spectral Radiometer) as advanced work to use satellite image data. That is, damage of a forest fire by the naked eye observation was divided into the No damage, the light damage, the serious damage and we estimated activity of forest and grasped revival possibility of forest. Through correlation analysis between the spectral reflectance by SPM and the near infrared CCD camera, we could get high correlation in the No damage and light damage. Therefore, when we surveyed damage of a forest fire, we could grasp damage, that is hardly observed by the naked eye by, using jointly the spectral radiometer and the near infrared CCD camera.

Development of PKNU3: A small-format, multi-spectral, aerial photographic system

  • Lee Eun-Khung;Choi Chul-Uong;Suh Yong-Cheol
    • Korean Journal of Remote Sensing
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    • v.20 no.5
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    • pp.337-351
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    • 2004
  • Our laboratory originally developed the compact, multi-spectral, automatic aerial photographic system PKNU3 to allow greater flexibility in geological and environmental data collection. We are currently developing the PKNU3 system, which consists of a color-infrared spectral camera capable of simultaneous photography in the visible and near-infrared bands; a thermal infrared camera; two computers, each with an 80-gigabyte memory capacity for storing images; an MPEG board that can compress and transfer data to the computers in real-time; and the capability of using a helicopter platform. Before actual aerial photographic testing of the PKNU3, we experimented with each sensor. We analyzed the lens distortion, the sensitivity of the CCD in each band, and the thermal response of the thermal infrared sensor before the aerial photographing. As of September 2004, the PKNU3 development schedule has reached the second phase of testing. As the result of two aerial photographic tests, R, G, B and IR images were taken simultaneously; and images with an overlap rate of 70% using the automatic 1-s interval data recording time could be obtained by PKNU3. Further study is warranted to enhance the system with the addition of gyroscopic and IMU units. We evaluated the PKNU 3 system as a method of environmental remote sensing by comparing each chlorophyll image derived from PKNU 3 photographs. This appraisement was backed up with existing study that resulted in a modest improvement in the linear fit between the measures of chlorophyll and the RVI, NDVI and SAVI images stem from photographs taken by Duncantech MS 3100 which has same spectral configuration with MS 4000 used in PKNU3 system.

Analysis of Forest Cover Information Extracted by Spectral Mixture Analysis (분광혼합분석 기법에 의한 산림피복 정보의 특성 분석)

  • 이지민;이규성
    • Korean Journal of Remote Sensing
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    • v.19 no.6
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    • pp.411-419
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    • 2003
  • An area corresponding to the spatial resolution of optical remote sensor imagery often includes more than one pure surface material. In such case, a pixel value represents a mixture of spectral reflectance of several materials within it. This study attempts to apply the spectral mixture analysis on forest and to evaluate the information content of endmember fractions resulted from the spectral unmixing. Landsat-7 ETM+ image obtained over the study area in the Kwangneung Experimental Forest was initially geo-referenced and radiometrically corrected to reduce the atmospheric and topographic attenuations. Linear mixture model was applied to separate each pixel by the fraction of six endmember: deciduous, coniferous, soil, built-up, shadow, and rice/grass. The fractional values of six endmember could be used to separate forest cover in more detailed spatial scale. In addition, the soil fraction can be further used to extract the information related to the canopy closure. We also found that the shadow effect is more distinctive at coniferous stands.

IMAGE SIMULATIONS OF THE KVN AND EAST ASIA VLBI FACILITIES WITH A SiO MASER MODEL IMAGE (KVN과 동아시아 VLBI 관측시설을 이용한 SiO 메이저 모델이미지 모의실험)

  • Yi, Ji-Yun;Jung, Tae-Hyun
    • Publications of The Korean Astronomical Society
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    • v.25 no.1
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    • pp.15-21
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    • 2010
  • We report results of image simulations of the KVN and VLBI experiments of the KVN with several other East Asia VLBI facilities. To investigate their imaging capability a model-generated image of 7 mm SiO maser emission in Mira variables is used. The resulting simulations show that the joint VLBI experiments of the KVN with East Asia VLBI facilities can produce reasonably good images at 7 mm spectral line experiments. However, there are no apparent differences in peak flux densities and images themselves in the simulations among different combinations of these facilities. In addition, the simulated images of observations which include bigger antennas do not show any expected improvement to the image sensitivity. The small variations in the peak flux density and similar image sensitivity, irrespective of different antenna sizes or numbers of baselines used in the simulations, turn out due to a specific characteristic of the adopted model image. Test simulations using another SiO maser image from R Cas observations prove that the participation of bigger antennas in the VLBI experiments does improve image sensitivity. We confirm the need of additional longer baselines in the experiments of the East Asia VLBI facilities to study very compact maser clumps on sub-milliarcsecond scales.

Color Image Enhancement Using Local Area Histogram Equalization On Segmented Regions Via Watershed Transform

  • Lertpokanont, B.;Chitwong, S.;Cheevasuvit, F.;Dejhan, K.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.192-194
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    • 2003
  • Since the details in quasi-homogeneous region will be destroyed from the conventional global image enhancement method such as histogram equalization. This defect is caused by the saturation of gray level in equalization process. So the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the region itself. To obtain the quasi- homogeneous regions, the original image must be segmented. Here we applied the watershed transform to the interesting image. Since the watershed transform is based on mathematical morphology, therefore, the regions touch can be effectively separated. Hence two adjacent regions which have the similar gray pixels will be split off. The process will be independently applied to three different spectral images. Then three different colors are assigned to each processed image in order to produce a color composite image. By the proposed algorithm, the result image shows the better perception on image details. Therefore, the high efficiency of image classification can be obtained by using this color image.

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