• Title/Summary/Keyword: Remotely sensed imagery

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A Comparative Study of 3D DWT Based Space-borne Image Classification for Differnet Types of Basis Function

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Korean Journal of Remote Sensing
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    • v.24 no.1
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    • pp.57-64
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    • 2008
  • In the previous study, the Haar wavelet was used as the sole basis function for the 3D discrete wavelet transform because the number of bands is too small to decompose a remotely sensed image in band direction with other basis functions. However, it is possible to use other basis functions for wavelet decomposition in horizontal and vertical directions because wavelet decomposition is independently performed in each direction. This study aims to classify a high spatial resolution image with the six types of basis function including the Haar function and to compare those results. The other wavelets are more helpful to classify high resolution imagery than the Haar wavelet. In overall accuracy, the Coif4 wavelet has the best result. The improvement of classification accuracy is different depending on the type of class and the type of wavelet. Using the basis functions with long length could be effective for improving accuracy in classification, especially for the classes of small area. This study is expected to be used as fundamental information for selecting optimal basis function according to the data properties in the 3D DWT based image classification.

The change of land cover classification accuracies according to spatial resolution in case of Sunchon bay coastal wetland (위성영상 해상도에 따른 순천만 해안습지의 분류 정확도 변화)

  • Ku, Cha-Yong;Hwang, Chul-Sue
    • Journal of the Korean association of regional geographers
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    • v.7 no.1
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    • pp.35-50
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    • 2001
  • Since remotely sensed images of coastal wetlands are very sensitive to spatial resolution, it is very important to select an optimum resolution for particular geographic phenomena needed to be represented. Scale is one of the most important factors in spatial analysis techniques, which is defined as a spatial and temporal interval for a measurement or observation and is determined by the spatial extent of study area or the measurement unit. In order to acquire the optimum scale for a particular subject (i.e., coastal wetlands), measuring and representing the characteristics of attribute information extracted from the remotely sensed images are required. This study aims to explore and analyze the scale effects of attribute information extracted from remotely sensed coastal wetlands images. Specifically, it is focused on identifying the effects of scale in response to spatial resolution changes and suggesting a methodology for exploring the optimum spatial resolution. The LANDSAT TM image of Sunchon Bay was classified by a supervised classification method, Six land cover types were classified and the Kappa index for this classification was 84.6%. In order to explore the effects of scale in the classification procedure, a set of images that have different spatial resolutions were created by a aggregation method. Coarser images were created with the original image by averaging the DN values of neighboring pixels. Sixteen images whose resolution range from 30 m to 480 m were generated and classified to obtain land cover information using the same training set applied to the initial classification. The values of Kappa index show a distinctive pattern according to the spatial resolution change. Up to 120m, the values of Kappa index changed little, but Kappa index decreased dramatically at the 150m. However, at the resolution of 240 m and 270m, the classification accuracy was increased. From this observation, the optimum resolution for the study area would be either at 240m or 270m with respect to the classification accuracy and the best quality of attribute information can be obtained from these resolutions. Procedures and methodologies developed from this study would be applied to similar kinds and be used as a methodology of identifying and defining an optimum spatial resolution for a given problem.

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Classification with Seasonal Variability using Harmonic Components: Application for Remotely-sensed Images of Korean Peninsula

  • Lee, Sang-Hoon;Hong, Hyun-Ki
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1483-1485
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    • 2003
  • Multitemporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. Using the estimates of periodogram which are obtained from sequential images, the periodicity of the process have been incorporates into multitemporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for seven-day composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 - 2000 using a dynamic technique.

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SWT -based Wavelet Filter Application for De-noising of Remotely Sensed Imageries

  • Yoo Hee-Young;Lee Kiwon;Kwon Byung-Doo
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.505-508
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    • 2005
  • Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

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Directional texture information for connecting road segments in high spatial resolution satellite images

  • Lee, Jong-Yeol
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.245-245
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    • 2005
  • This paper addresses the use of directional textural information for connecting road segments. In urban scene, some roads are occluded by buildings, casting shadow of buildings, trees, and cars on streets. Automatic extraction of road network from remotely sensed high resolution imagery is generally hindered by them. The results of automatic road network extraction will be incomplete. To overcome this problem, several perceptual grouping algorithms are often used based on similarity, proximity, continuation, and symmetry. Roads have directions and are connected to adjacent roads with certain angles. The directional information is used to guide road fragments connection based on roads directional inertia or characteristics of road junctions. In the primitive stage, roads are extracted with textural and direction information automatically with certain length of linearity. The primitive road fragments are connected based on the directional information to improve the road network. Experimental results show some contribution of this approach for completing road network, specifically in urban area.

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A Study on Linear Spectral Mixing Model for Hyperspectral Imagery with Geometric Method (기하학적 기법을 이용한 하이퍼스펙트럴 영상의 Linear Spectral Mixing모델에 관한 연구)

  • 장은석;김대성;김용일
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.11a
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    • pp.23-29
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    • 2003
  • Detection in remotely sensed images can be conducted spatially, spectrally or both [2]. If the images have high spatial resolution, materials can be detected by using spatial and spectral information, unless we can't see the object embedded in a pixel. In this paper, we intend to solve the limit of spatial resolution by using the hyperspectral image which has high spectral resolution. Therefore, the Linear Spectral Mixing(LSM) Model which is sub-pixel detection algorithm is used to solve this problem. To find class Endmembers, we applied Geometric Model with MNF(Minimum Noise Fraction) transformation. From the result of sub-pixel detection algorithm, we can see the detection of water is satisfied and the object shape cannot be extracted but the possibility of material existence can be identified.

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A Study of Sub-Pixel Detection for Hyperspectral Image Using Linear Spectral Unmixing Algorithm (Linear Spectral Unmixing 기법을 이용한 하이퍼스펙트럴 영상의 Sub-Pixel Detection에 관한 연구)

  • 김대성;조영욱;한동엽;김용일
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.04a
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    • pp.161-166
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    • 2003
  • Hyperspectral imagery have high spectral resolution and provide the potential for more accurate and detailed information extraction than any other type of remotely sensed data. In this paper, the "Linear Spectral Unmixing" model which is one solution to overcome the limit of spatial resolution for remote sensing data was introduced and we applied the algorithm to hyperspectral image. The result was not good because of some problems such as image calibration and used endmembers. Therefore, we analyzed the cause and had a search for a solution.

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Analysis of Daejeon Metropolitan City′s Urbanized Area Change Pattern using Remotely Sensed Imagery (위성자료를 이용한 대전시 도시지역 변화특성 연구)

  • 김윤수;이광재
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.279-285
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    • 2004
  • 도시라는 광역지역의 확장을 분석하는데 위성자료는 매우 유용한 정보를 제공한다. 특히 한국항공우주연구원에서 운용중인 다목적 실용위성(KOMPSAT) 1호 영상자료는 해상도가 높아 도시지역의 분석에 유용한 정보를 제공하고 있으며, 과거의 항공사진 등을 복합적으로 활용한다면 도시의 확장 과정에 대한 시계열 분석이 가능하다. 도시의 확장 과정을 분석하여 그 정보를 추출하는 것은 새로운 도시계획을 위한 필수적인 기본 자료를 구축하는 중요한 역할을 할 수 있으며, 특히 2003년 개정 시행중인 국토의 계획 및 이용에 관한 법률은 도시기본계획 수립에 있어 도시의 성장 경향 등에 관한 기초조사를 의무화한 토지적성평가 제도를 도입하고 있다. 본 연구에서는 다목적 실용위성 1호 EOC 영상과 기타 원격탐사 자료를 복합적으로 활용하여 대전광역시 도시화 지역의 확장 추이를 분석하고 그 경향과 특성을 도출해 도시계획 수립에 원격탐사 자료를 활용할 수 있는 가능성을 제시해 보고자 한다.

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Image Change Tracking System (영상 변화 추적 시스템)

  • Park Young-Hwan
    • Geophysics and Geophysical Exploration
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    • v.2 no.3
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    • pp.154-158
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    • 1999
  • This paper introduces a partial edge detection technique, that improves the processing time of an automatic change tracking system for multi-temporal images. In the conventional change tracking systems for multi-temporal images, the edge detection is performed over the whole image. In the proposed method, however, the necessary portions for the edge detection is selected first and the edge detection is performed over the selected parts only. As a consequence, the improvement in the processing time could be achieved. The proposed change tracking system is expected to be utilized as a very efficient tool to configure changes in large data set such as remotely sensed satellite imagery or geophysical time laps images.

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Comparison of Visual Interpretation and Image Classification of Satellite Data

  • Lee, In-Soo;Shin, Dong-Hoon;Ahn, Seung-Mahn;Lee, Kyoo-Seock;Jeon, Seong-Woo
    • Korean Journal of Remote Sensing
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    • v.18 no.3
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    • pp.163-169
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    • 2002
  • The land uses of Korean peninsula are very complicated and high-density. Therefore, the image classification using coarse resolution satellite images may not provide good results for the land cover classification. The purpose of this paper is to compare the classification accuracy of visual interpretation with that of digital image classification of satellite remote sensing data such as 20m SPOT and 30m TM. In this study, hybrid classification was used. Classification accuracy was assessed by comparing each classification result with reference data obtained from KOMPSAT-1 EOC imagery, air photos, and field surveys.