• Title/Summary/Keyword: SATELLITE IMAGE

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Implementation of Matrix Receiving Structure for Versatile Multi-Mission LEO Operations (저궤도 다중위성 운용을 위한 매트릭스 구조의 수신 채널 구현)

  • Park, Durk-Jong;Yeom, Kyung-Whan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.24 no.10
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    • pp.1001-1007
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    • 2013
  • In the case of multi-mission LEO(Low Earth Orbit) operations, depending on the orbit of each satellite, one ground site is supposed to be communicated with more than two satellites at the same time. On top of that, image data processing system is generally mission-specific and 1:1 backup configuration. For the reason, if ground site has smaller number of antenna than that of satellite, interface with image data processing system would be very complicated. In this paper, considering that two LEO satellites can be operating and image data recording unit in redundancy can be easily plug-in, the implementation of matrix receiving structure is described. This matrix receiving structure has been validated from KOMPSAT-2 and -3(KOrea Multi-Purpose SATellite-2 and -3) since KOMPSAT-3 was launched in May, 2012. This structure will be applied for the KOMPSAT-3A and -5 through its expandability.

Fine Registration between Very High Resolution Satellite Images Using Registration Noise Distribution (등록오차 분포특성을 이용한 고해상도 위성영상 간 정밀 등록)

  • Han, Youkyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.3
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    • pp.125-132
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    • 2017
  • Even after applying an image registration, Very High Resolution (VHR) multi-temporal images acquired from different optical satellite sensors such as IKONOS, QuickBird, and Kompsat-2 show a local misalignment due to dissimilarities in sensor properties and acquisition conditions. As the local misalignment, also referred to as Registration Noise (RN), is likely to have a negative impact on multi-temporal information extraction, detecting and reducing the RN can improve the multi-temporal image processing performance. In this paper, an approach to fine registration between VHR multi-temporal images by considering local distribution of RN is proposed. Since the dominant RN mainly exists along boundaries of objects, we use edge information in high frequency regions to identify it. In order to validate the proposed approach, datasets are built from VHR multi-temporal images acquired by optical satellite sensors. Both qualitative and quantitative assessments confirm the effectiveness of the proposed RN-based fine registration approach compared to the manual registration.

Pattern Classification of Multi-Spectral Satellite Images based on Fusion of Fuzzy Algorithms (퍼지 알고리즘의 융합에 의한 다중분광 영상의 패턴분류)

  • Jeon, Young-Joon;Kim, Jin-Il
    • Journal of KIISE:Software and Applications
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    • v.32 no.7
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    • pp.674-682
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    • 2005
  • This paper proposes classification of multi-spectral satellite image based on fusion of fuzzy G-K (Gustafson-Kessel) algorithm and PCM algorithm. The suggested algorithm establishes the initial cluster centers by selecting training data from each category, and then executes the fuzzy G-K algorithm. PCM algorithm perform using classification result of the fuzzy G-K algorithm. The classification categories are allocated to the corresponding category when the results of classification by fuzzy G-K algorithm and PCM algorithm belong to the same category. If the classification result of two algorithms belongs to the different category, the pixels are allocated by Bayesian maximum likelihood algorithm. Bayesian maximum likelihood algorithm uses the data from the interior of the average intracluster distance. The information of the pixels within the average intracluster distance has a positive normal distribution. It improves classification result by giving a positive effect in Bayesian maximum likelihood algorithm. The proposed method is applied to IKONOS and Landsat TM remote sensing satellite image for the test. As a result, the overall accuracy showed a better outcome than individual Fuzzy G-K algorithm and PCM algorithm or the conventional maximum likelihood classification algorithm.

Comparison of Orbit-attitude Model between Spot and Kompsat-2 Imagery (Spot 영상과 Kompsat-2 영상에서의 궤도 자세각 모델의 성능 비교)

  • Jeong, Jae-Hoon;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • v.25 no.2
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    • pp.133-143
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    • 2009
  • This paper describes differences of performance when the orbit attitude model is applied to the respective images obtained from two different types of satellite. The one is Spot that rotates its pointing mirror and the other is Kompsat-2 that rotates its whole body when they obtain imagery for target. Our research scope is limited to the orbit-attitude model only as its good performance was proved in prior investigation. Model performances between two images were compared with sensor model accuracy and 3D coordinates calculation. The results show performances of the orbit-attitude model for each image type were different. For Spot imagery, the model required attitude angle to be included as adjustment parameters. For Kompsat-2 imagery, the model required high-order parameter for adjustment. This implies that satellite sensor model may be applied differently in accordance with platform's attitude control scheme and accuracy. Understanding of this information can be a base for improvement and development of model and application for new satellite images.

Multi-Image RPCs Sensor Modeling of High-Resolution Satellite Images Without GCPs (고해상도 위성영상 무기준점 기반 다중영상 센서 모델링)

  • Oh, Jae Hong;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.533-540
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    • 2021
  • High-resolution satellite images have high potential to acquire geospatial information over inaccessible areas such as Antarctica. Reference data are often required to increase the positional accuracy of the satellite data but the data are not available in many inland areas in Antarctica. Therefore this paper presents a multi-image RPCs (Rational Polynomial Coefficients) sensor modeling without any ground controls or reference data. Conjugate points between multi-images are extracted and used for the multi-image sensor modeling. The experiment was carried out for Kompsat-3A and showed that the significant accuracy increase was not observed but the approach has potential to suppress the maximum errors, especially the vertical errors.

Building Change Detection Methodology in Urban Area from Single Satellite Image (단일위성영상 기반 도심지 건물변화탐지 방안)

  • Seunghee Kim;Taejung Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1097-1109
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    • 2023
  • Urban is an area where small-scale changes to individual buildings occur frequently. An existing urban building database requires periodic updating to increase its usability. However, there are limitations in data collection for building changes over a wide urban. In this study, we check the possibility of detecting building changes and updating a building database by using satellite images that can capture a wide urban region by a single image. For this purpose, building areas in a satellite image are first extracted by projecting 3D coordinates of building corners available in a building database onto the image. Building areas are then divided into roof and facade areas. By comparing textures of the roof areas projected, building changes such as height change or building removal can be detected. New height values are estimated by adjusting building heights until projected roofs align to actual roofs observed in the image. If the projected image appeared in the image while no building is observed, it corresponds to a demolished building. By checking buildings in the original image whose roofs and facades areas are not projected, new buildings are identified. Based on these results, the building database is updated by the three categories of height update, building deletion, or new building creation. This method was tested with a KOMPSAT-3A image over Incheon Metropolitan City and Incheon building database available in public. Building change detection and building database update was carried out. Updated building corners were then projected to another KOMPSAT-3 image. It was confirmed that building areas projected by updated building information agreed with actual buildings in the image very well. Through this study, the possibility of semi-automatic building change detection and building database update based on single satellite image was confirmed. In the future, follow-up research is needed on technology to enhance computational automation of the proposed method.

A Study on Object Based Image Analysis Methods for Land Use and Land Cover Classification in Agricultural Areas (변화지역 탐지를 위한 시계열 KOMPSAT-2 다중분광 영상의 MAD 기반 상대복사 보정에 관한 연구)

  • Yeon, Jong-Min;Kim, Hyun-Ok;Yoon, Bo-Yeol
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.3
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    • pp.66-80
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    • 2012
  • It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.

Determination of Spatial Resolution to Improve GCP Chip Matching Performance for CAS-4 (농림위성용 GCP 칩 매칭 성능 향상을 위한 위성영상 공간해상도 결정)

  • Lee, YooJin;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1517-1526
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    • 2021
  • With the recent global and domestic development of Earth observation satellites, the applications of satellite images have been widened. Research for improving the geometric accuracy of satellite images is being actively carried out. This paper studies the possibility of automated ground control point (GCP) generation for CAS-4 satellite, to be launched in 2025 with the capability of image acquisition at 5 m ground sampling distance (GSD). In particular, this paper focuses to check whether GCP chips with 25 cm GSD established for CAS-1 satellite images can be used for CAS-4 and to check whether optimalspatial resolution for matching between CAS-4 images and GCP chips can be determined to improve matching performance. Experiments were carried out using RapidEye images, which have similar GSD to CAS-4. Original satellite images were upsampled to make satellite images with smaller GSDs. At each GSD level, up-sampled satellite images were matched against GCP chips and precision sensor models were estimated. Results shows that the accuracy of sensor models were improved with images atsmaller GSD compared to the sensor model accuracy established with original images. At 1.25~1.67 m GSD, the accuracy of about 2.4 m was achieved. This finding lead that the possibility of automated GCP extraction and precision ortho-image generation for CAS-4 with improved accuracy.

Method for Restoring the Spatial Resolution of KOMPSAT-3A MIR Image (KOMPSAT-3A 중적외선 영상의 공간해상도 복원 기법)

  • Oh, Kwan-Young;Lee, Kwang-Jae;Jung, Hyung-Sup;Park, Sung-Hwan;Kim, Jeong-Cheol
    • Korean Journal of Remote Sensing
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    • v.35 no.6_4
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    • pp.1391-1401
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    • 2019
  • The KOMPSAT-3A is a high-resolution optical satellite launched in 2015 by Korea Aerospace Research Institute (KARI). KOMPSAT-3A provides Panchromatic (PAN-0.55 m), Multispectral (MS-2.2 m), and Mid-wavelength infrared (MIROR-5.5 m) image. However, due to security or military problems, MIROR image with 5.5m spatial resolution are provided down sampled at 33 m spatial resolution (MIRrd). In this study, we propose spatial sharpening method to improve the spatial resolution of MIRrd image (33 m) using virtual High Frequency (HF) image and optimal fusion factor. Using MS image and MIRrd image, we generated virtual high resolution (5.5 m) MIRORfus image and then compared them to actual high-resolution MIROR image. The test results show that the proposed method merges the spatial resolution of MS image and the spectral information of MIRrd image efficiently.

Wavelet Packet Image Coder Using Coefficients Partitioning For Remote Sensing Images (위성 영상을 위한 계수분할 웨이블릿 패킷 영상 부호화 알고리즘에 관한 연구)

  • 한수영;조성윤
    • Korean Journal of Remote Sensing
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    • v.18 no.6
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    • pp.359-367
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    • 2002
  • In this paper, a new embedded wavelet packet image coder algorithm is proposed for an effective image coder using correlation between partitioned coefficients. This new algorithm presents parent-child relationship for reducing image reconstruction error using relations between individual frequency sub-bands. By parent-child relationship, every coefficient is partitioned and encoded for the zerotree data structure. It is shown that the proposed wavelet packet image coder algorithm achieves low bit rates and rate-distortion. It also demonstrates higher PSNR under the same bit rate and an improvement in image compression time. The perfect rate control is compared with the conventional method. These results show that the encoding and decoding processes of the proposed coder are simpler and more accurate than the conventional ones for texture images that include many mid and high-frequency elements such as aerial and satellite photograph images. The experimental results imply the possibility that the proposed method can be applied to real-time vision system, on-line image processing and image fusion which require smaller file size and better resolution.