• 제목/요약/키워드: Remote sensing images

검색결과 1,721건 처리시간 0.023초

EVOLUTION OF INTERNAL WAVES NEAR A TURNING POINT IN THE SOUTH CHINA SEA USING SAR IMAGERY AND NUMERICAL MODELS

  • Kim, Duk-Jin;Lyzenga, David R.;Choi, Woo-Young;Kim, Youn-Soo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.61-64
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    • 2007
  • Subsurface Internal Waves (IWs) can be detected in satellite images as periodic alternating brighter/darker stripes. It is known that there are two types of IWs - depression type and elevation type - depending on the water depth in stratified oceans. In this study, we have quantitatively verified the process of converting polarity from depression waves to elevation waves using ERS-2 SAR images acquired over the northern South China Sea. We simulated the evolution of IWs near a turning point with a numerical model for internal wave propagation. The simulation results near the turning point clearly showed us not only a conversion process of IWs from depression to elevation waves, but also a similar wave pattern with the observed SAR image. We also simulated SAR intensity variation near the turning point. The upper layer currents were computed at regular intervals using the numerical model, as the IWs were passing through the turning point. Then, an integrated hydrodynamic-electromagnetic model was used for simulating SAR intensity profiles from the upper layer currents at each position. The simulated SAR intensity profiles at each position were compared with the observed SAR intensities.

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위성 안개 영상을 위한 강인한 특징점 검출 기반의 영상 정합 (Image Matching Based on Robust Feature Extraction for Remote Sensing Haze Images)

  • 권오설
    • 방송공학회논문지
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    • 제21권2호
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    • pp.272-275
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    • 2016
  • 본 논문은 위성 영상을 위한 안개 제거 및 표면반사율 기반의 특징점 검출 방법을 제안한다. 기존의 안개 제거를 위한 DCP 방법은 패치 기반의 처리 방식으로 인해 전달맵 생성 과정에서 블록현상이 발생하게 되고, 이는 영상을 흐리게 하는 원인이 된다. 따라서 제안한 은닉마코프 기반의 방법은 영상의 블록 현상을 제거하고 선명도를 향상한다. 또한 표면반사율 기반의 견고한 특징점 추출을 통해서 영상 정합의 정확성을 향상하였다. 실험을 통해 제안한 방법이 기존 방법에 비해 안개 제거의 성능에서 우수함을 확인하였으며 이를 통해 특징 검출 및 위성 영상 정합에 적합함을 확인하였다.

A Prototype Implementation for 3D Animated Anaglyph Rendering of Multi-typed Urban Features using Standard OpenGL API

  • Lee, Ki-Won
    • 대한원격탐사학회지
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    • 제23권5호
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    • pp.401-408
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    • 2007
  • Animated anaglyph is the most cost-effective method for 3D stereo visualization of virtual or actual 3D geo-based data model. Unlike 3D anaglyph scene generation using paired epipolar images, the main data sets of this study is the multi-typed 3D feature model containing 3D shaped objects, DEM and satellite imagery. For this purpose, a prototype implementation for 3D animated anaglyph using OpenGL API is carried out, and virtual 3D feature modeling is performed to demonstrate the applicability of this anaglyph approach. Although 3D features are not real objects in this stage, these can be substituted with actual 3D feature model with full texture images along all facades. Currently, it is regarded as the special viewing effect within 3D GIS application domains, because just stereo 3D viewing is a part of lots of GIS functionalities or remote sensing image processing modules. Animated anaglyph process can be linked with real-time manipulation process of 3D feature model and its database attributes in real world problem. As well, this approach of feature-based 3D animated anaglyph scheme is a bridging technology to further image-based 3D animated anaglyph rendering system, portable mobile 3D stereo viewing system or auto-stereo viewing system without glasses for multi-viewers.

Selecting Optimal Basis Function with Energy Parameter in Image Classification Based on Wavelet Coefficients

  • Yoo, Hee-Young;Lee, Ki-Won;Jin, Hong-Sung;Kwon, Byung-Doo
    • 대한원격탐사학회지
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    • 제24권5호
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    • pp.437-444
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    • 2008
  • Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have tried to enhance classification accuracy. Previous studies have shown that the classification technique based on wavelet transform is more effective than traditional techniques based on original pixel values, especially in complicated imagery. Various basis functions such as Haar, daubechies, coiflets and symlets are mainly used in 20 image processing based on wavelet transform. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we first computed the wavelet coefficients of satellite image using ten different basis functions, and then classified images. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis functions. The energy parameters of wavelet detail bands and overall accuracy are clearly correlated. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

ERS-1 AND CCRS C-SAR Data Integration For Look Direction Bias Correction Using Wavelet Transform

  • Won, J.S.;Moon, Woo-Il M.;Singhroy, Vern;Lowman, Paul-D.Jr.
    • 대한원격탐사학회지
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    • 제10권2호
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    • pp.49-62
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    • 1994
  • Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

Keypoint-based Deep Learning Approach for Building Footprint Extraction Using Aerial Images

  • Jeong, Doyoung;Kim, Yongil
    • 대한원격탐사학회지
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    • 제37권1호
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    • pp.111-122
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    • 2021
  • Building footprint extraction is an active topic in the domain of remote sensing, since buildings are a fundamental unit of urban areas. Deep convolutional neural networks successfully perform footprint extraction from optical satellite images. However, semantic segmentation produces coarse results in the output, such as blurred and rounded boundaries, which are caused by the use of convolutional layers with large receptive fields and pooling layers. The objective of this study is to generate visually enhanced building objects by directly extracting the vertices of individual buildings by combining instance segmentation and keypoint detection. The target keypoints in building extraction are defined as points of interest based on the local image gradient direction, that is, the vertices of a building polygon. The proposed framework follows a two-stage, top-down approach that is divided into object detection and keypoint estimation. Keypoints between instances are distinguished by merging the rough segmentation masks and the local features of regions of interest. A building polygon is created by grouping the predicted keypoints through a simple geometric method. Our model achieved an F1-score of 0.650 with an mIoU of 62.6 for building footprint extraction using the OpenCitesAI dataset. The results demonstrated that the proposed framework using keypoint estimation exhibited better segmentation performance when compared with Mask R-CNN in terms of both qualitative and quantitative results.

위성영상의 종류에 따른 분리도 특성의 상관관계 분석 (Analysis of Relation of Class Separability According to Different Kind of Satellite Images)

  • 홍순헌
    • 한국콘텐츠학회논문지
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    • 제7권1호
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    • pp.215-224
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    • 2007
  • 위성영상의 분류는 원격탐사의 가장 기본적인 분야이다. 위성영상분리도 위성영상의 분류에 있어 영상 정확도 향상에 매우 효율적이라 할 수 있다. 영상분류를 향상시키기 위해서 분리도의 특성을 파악하여 분류의 정확도와의 상관관계를 분석하였다. 영상은 영상마다의 분리도를 비교, 분석하기 위해 IKONOS 영상, SPOT 5 영상, Landsat IM 영상을 1m의 해상도로 리샘플링하였다. 본 연구에서 위성영상별로 클래스 분리도를 측정한 결과 분리도 값이 대체로 $1,600{\sim}2,000$으로 높게 나타났다.

원격탐사의 동향과 고해상도 위성영상의 활용 (The Trends in Remote Sensing and the Applications of High Resolution Space Images)

  • 여화수;박경환;박병욱
    • Spatial Information Research
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    • 제5권1호
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    • pp.89-98
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    • 1997
  • 원격탐사는 1972년이래 꾸준히 발전을 거듭해와 오늘날 고해상도의 위성영상을 수집하는 단계에까지 이르렀다. 고해상도 위성영상은 1m 이하의 공간 해상력을 갖는 영상으로 98년도부터 본격적인 공급이 시작될 것이며, 이것은 지도제작 분야를 비롯하여 측량, 정부 또는 자치단체, 가스/전력회사, 수자원 관리, 통신, 농업 등 여러 분야에서 다양하게 활용될 것이다. 특히 지도제작 분야에 있어서는 고해상도 위성영상을 이용하므로서 기존의 항공사진을 이용하는 지도제작 방법을 혁명적으로 바꾸게 될 것이다. 따라서 본고에서는 이러한 최신기술의 동향과 그 기술의 활용방안에 대하여 검토하고자 하였다.

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Atmospheric Correction Problems with Multi-Temporal High Spatial Resolution Images from Different Satellite Sensors

  • Lee, Hwa-Seon;Lee, Kyu-Sung
    • 대한원격탐사학회지
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    • 제31권4호
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    • pp.321-330
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    • 2015
  • Atmospheric correction is an essential part in time-series analysis on biophysical parameters of surface features. In this study, we tried to examine possible problems in atmospheric correction of multitemporal High Spatial Resolution (HSR) images obtained from two different sensor systems. Three KOMPSAT-2 and two IKONOS-2 multispectral images were used. Three atmospheric correction methods were applied to derive surface reflectance: (1) Radiative Transfer (RT) - based absolute atmospheric correction method, (2) the Dark Object Subtraction (DOS) method, and (3) the Cosine Of the Uun zeniTh angle (COST) method. Atmospheric correction results were evaluated by comparing spectral reflectance values extracted from invariant targets and vegetation cover types. In overall, multi-temporal reflectance from five images obtained from January to December did not show consistent pattern in invariant targets and did not follow a typical profile of vegetation growth in forests and rice field. The multi-temporal reflectance values were different by sensor type and atmospheric correction methods. The inconsistent atmospheric correction results from these multi-temporal HSR images may be explained by several factors including unstable radiometric calibration coefficients for each sensor and wide range of sun and sensor geometry with the off-nadir viewing HSR images.

누적 유사도 측정을 이용한 자동 임계값 결정 기법 - 다중분광 및 초분광영상의 무감독 변화탐지를 목적으로 (Automatic Thresholding Method using Cumulative Similarity Measurement for Unsupervised Change Detection of Multispectral and Hyperspectral Images)

  • 김대성;김형태
    • 대한원격탐사학회지
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    • 제24권4호
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    • pp.341-349
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    • 2008
  • 본 논문은 위성영상을 이용한 변화정보를 취득하는데 있어 중요한 과정인 임계값 결정에 관한 새로운 기법을 제안하고 있다. 화소간 유사도 측정을 통해 도출된 결과 값을 일정 간격으로 누적 계산하고, 급격하게 변하는 지점을 임계값으로 결정하였다. 의사영상을 통해 기대최대화 기법, 교점방법과 성능을 비교하였으며, 두 시기의 ALI 영상과 Hyperion 영상에 실제 적용하여 변화탐지 결과를 확인하였다. 제안된 기법은 기존의 기법과 비슷한 수준의 변화탐지 결과 정확도를 확보할 수 있었으며, 기대최대화 기법에 비해 간단하게 적용할 수 있고, 교점방법과 달리 최빈 값을 둘 이상 가지는 히스토그램에도 적용할 수 있는 장점이 있어 향후 변화유무 정보 취득에 효과적으로 사용할 수 있을 것으로 기대한다.