• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.526-529
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• 2007

Due to its inherent feature of high-resolution satellite, there is strong need in some specific area to minimize the processing time required to get a standard image on hand from downlink signal acquisition. However, in general image processing system, it takes considerable time to get image data up to certain level from raw data acquisition because the huge amount of data is dealt sequentially as input data. This paper introduces the high-speed image processing system which generates the image data only for the area selected by user. To achieve the high speed performance, this system includes Quick Look Image display function with sampling, ROI selection function, Image Line Index function, and Distributed processing function. The developed RPS was applied to KOMPSAT-2 320Mbps downlink channel and its effectiveness was successfully demonstrated. This feature to provide the image product very quickly is expected to promote the application of high resolution satellite image.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.101-116
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• 2012

In this paper, we have surveyed the existing architectures of the image processing systems for several meteorological satellites and identified issues which are taken into consideration to construct the advanced meteorological satellite image processing system that is being developed by NMSC(National Meteorological Satellite Center). Most of the existing systems provide the functionalities of the image acquisition, the image processing, the data management, and the data dissemination. Those systems have some common problems with respect to system integration and system maintenance. To solve these problems, NOAA, NWS and ESA suggest new system architectures to improve the existing systems. This paper introduces domestic and foreign approaches to build the satellite image processing systems and studies some issues and strategies for developing those systems.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.49-52
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• 2002

High-resolution satellite image processing software should be able to ensure accurate, fast, compact data processing in offline or online environment. In this paper, component software for high-resolution satellite image processing is developed using OpenGIS components and real-time data processing architecture. The developed component software is composed of three major packages, which are data provide package, user interface package, and fast data processing package. The data provider package encodes and decodes diverse image/vector data formats and give identical data access methods to developers. The user interface package supports menus, toolbars, dialogs, and events to use easier. The fast data processing package follows the OpenGIS's data processing standards, which can deal with several processors as components with standard procedural functionalities.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.339-350
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• 2017

In recent, cloud computing paradigm and open source as a huge trend in the Information Communication Technology (ICT) are widely applied, being closely interrelated to each other in the various applications. The integrated services by both technologies is generally regarded as one of a prospective web-based business models impacting the concerned industries. In spite of progressing those technologies, there are a few application cases in the geo-based application domains. The purpose of this study is to develop a cloud-based service system for satellite image processing based on the pure and full open source. On the OpenStack, cloud computing open source, virtual servers for system management by open source stack and image processing functionalities provided by OTB have been built or constructed. In this stage, practical image processing functions for KOMPSAT within this service system are thresholding segmentation, pan-sharpening with multi-resolution image sets, change detection with paired image sets. This is the first case in which a government-supporting space science institution provides cloud-based services for satellite image processing functionalities based on pure open source stack. It is expected that this implemented system can expand with further image processing algorithms using public and open data sets.

• Korean Journal of Remote Sensing
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• v.5 no.1
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• pp.29-39
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• 1989

A study to develop generalized and systematically designed satellite image processing software system on mainframe computer was successfully carried out. Commercially available softwares such as LARSYS were analyzed and modified, and well known satellite data processing algorithms were implemented into comprehensive software. New algorithms were also presented and developed. The contents of developed softwere system may be divided into 8 major sections: menu and user interface, data file management, preprocessing, enhancement in monochrome image, multi-dimension image analysis, scene classification, image display/hardcopy, image handle utility software. Some additional software such as GIS and DBMS will make this software more comprehensive and generalized one for the satellite data processing.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.79-93
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• 2012

This paper suggests a system architecture for the advanced meteorological satellite image processing system that is developing by NMSC(National Meteorological Satellite Center). The meteorology satellite image processing system has basically the image acquisition, the image processing, the data management, and the data dissemination functionalities. However, the existing system has some problems with respect to system integration as well as maintenance to accommodate new satellites and/or the new image processing systems for them which will be developed in the near future. To cope with these problems we propose a new system architecture for the advanced meteorology satellite image processing system. To do this we select as the architectural drivers the quality attributes such as modifiability, inter-operability, extendability, reusability, and platform independency and design the architecture to achieve such quality attributes. We expect that the new approach will solve current issues such as system integration, system dependency, or data management problems and will provide easy ways to incorporate new systems and to maintain them.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.5
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• pp.427-435
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• 2018

Many countries are trying to deploy satellite surveillance systems for their national defense, and one of these system uses optical systems to observe the satellites above their territories. The optical satellite surveillance system requires the coordinates of the satellites in an acquired image and expects that those coordinates to be delivered to the tracking system. The proposed method detects the satellite sources in a high-resolution image with fast image processing for the optical surveillance system. To achieve faster detection, the proposed method reduces the size of the original image and approximates the trajectory of a satellite, so image processing methods are only applied to the nearby area of the approximated trajectory in the original image. The proposed method shows the similar detection performance faster than the previous method.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.372-380
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• 2022

This study proposes a distributed parallel processing system, called the Fast Analysis System for remote sensing daTa(FAST), for large-scale satellite image processing and analysis. FAST is a system that designs jobs in vertices and sequences, and distributes and processes them simultaneously. FAST manages data based on the Hadoop Distributed File System, controls entire jobs based on Apache Spark, and performs tasks in parallel in multiple slave nodes based on a docker container design. FAST enables the high-performance processing of progressively accumulated large-volume satellite images. Because the unit task is performed based on Docker, it is possible to reuse existing source codes for designing and implementing unit tasks. Additionally, the system is robust against software/hardware faults. To prove the capability of the proposed system, we performed an experiment to generate the original satellite images as ortho-images, which is a pre-processing step for all image analyses. In the experiment, when FAST was configured with eight slave nodes, it was found that the processing of a satellite image took less than 30 sec. Through these results, we proved the suitability and practical applicability of the FAST design.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.95-101
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• 2015

The backup site operation of the Image Data Acquisition and Control System (IDACS) for Communication Ocean Meteorological Satellite (COMS) is discussed in terms of the ground station configuration, image data processing, and the characteristics of backup activities for both the meteorological image data and the ocean image data. The well-performed backup operation of the COMS IDACS is also confirmed with the first three years normal operation results from April, 2011 to March, 2014. The operation results are analyzed through statistical approach to provide the achieved operational performance of the image data reception, preprocessing, and broadcast.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.573-577
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• 2002

The Landsat Program is the longest running enterprise for acquisition of imagery of the Earth from space. The first Landsat satellite was launched in 1972 and the most recent, Landsat 7, was launched on April 15, 1999. The Landsat satellites have acquired millions of images. The Landsat 7 receiving station is installed at more than 25 sites and will be installed in Korea. This paper will address the work being carried out for the development of image receiving and processing system for the Landsat 7 image data, which will be used at ground station of Landsat 7 in Korea.