• Title/Summary/Keyword: Multi-Resolution Model

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Need for introduction of MRM and analyzing the validity of applying MRM into Korean army war game simulations (MRM 도입필요성 및 육군 W/G 적용 타당성 분석)

  • Lee, Seung-Ho
    • Journal of the military operations research society of Korea
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    • v.31 no.1
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    • pp.42-57
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    • 2005
  • Korea DM&S(Defence Modeling & Simulation) development plan includes construction of a distributed simulation model which enables us to construct, operate, integrate and connect war game simulations. US DoD and IEEE set the HLA/RTI as the standard of distributed simulation model. HLA/RTI models each simulator as a Federate and group of them as a Federation. Simulation with the model shows interoperability and finally executes a war game simulation. Because of different resolutions and features, it is not satisfied 'interoperability' and 'reusability' of simulation perfectly MRM (Multi Resolution Modeling) has been introduced, and many developed countries including the United States have studied the technology to simulate the model with different resolutions. This thesis proposes the need for introduction of MRM and analyzes both technical and operational validity when we apply MRM model to army war game simulations. For these purposes, we 1) find MRM main issues with the study about MRM basic concepts and case studies of MRM's applications, 2) present the need of MRM and its relation with DM&S development plan, and 3) analyze its technical and operational validity when we apply MRM to an example, CHANG-JO21 and JEON-TOO21.

Correction of One-layer Solar Radiation Model by Multi-layer Line-by-line Solar Radiation Model (다층 상세 태양복사 모델에 의한 단층 태양복사 모델의 보정)

  • Jee, Joon-Bum;Lee, Won-Hak;Zo, Il-Sung;Lee, Kyu-Tae
    • Atmosphere
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    • v.21 no.2
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    • pp.151-162
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    • 2011
  • One-layer solar radiation(GWNU; Gangneung-Wonju National University) model is developed in order to resolve the lack of vertical observations and fast calculation with high resolution. GWNU model is based on IQBAL(Iqbal, 1983) and NREL(National Renewable Energy Laboratory) methods and corrected by precise multi-layer LBL(Line-by-line) model. Input data were used 42 atmospheric profiles from Garand et al.(2001) for calculation of global radiation by the Multi-layer and one-layer solar radiation models. GWNU model has error of about -0.10% compared with LBL model while IQBAL and NREL models have errors of about -3.92 and -2.57%, respectively. Global solar radiation was calculated by corrected GWNU solar model with satellites(MODIS, OMI and MTSAT-1R), RDPS model prediction data in Korea peninsula in 2009, and the results were compared to surface solar radiation observed by 22 KMA solar sites. All models have correlation($R^2$) of 0.91 with the observed hourly solar radiation, and root mean square errors of IQBAL, NREL and GWNU models are 69.16, 69.74 and $67.53W/m^2$, respectively.

A Test Result on the Positional Accuracy of Kompsat-3A Beta Test Images

  • Oh, Jae Hong;Seo, Doo Chun;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.2
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    • pp.133-142
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    • 2016
  • KOMPSAT-3A (KOrea Multi-Purpose SATellite-3A) was launched in March 25 2015 with specification of 0.5 meters resolution panchromatic and four 2.2 meters resolution multi spectral sensors in 12km swath width at nadir. To better understand KOMPSAT-3A positional accuracy, this paper reports a test result on the accuracy of recently released KOMPSAT-3A beta test images. A number of ground points were acquired from 1:1,000 digital topographic maps over the target area for the accuracy validation. First, the original RPCs (Rational Polynomial Coefficients) were validated without any GCPs (Ground Control Points). Then we continued the test by modeling the errors in the image space using shift-only, shift and drift, and the affine model. Ground restitution accuracy was also analyzed even though the across track image pairs do not have optimal convergence angle. The experimental results showed that the shift and drift-based RPCs correction was optimal showing comparable accuracy of less than 1.5 pixels with less GCPs compared to the affine model.

Spaceborne High Speed Data Link Design for Multi-Mode SAR Image Data Transmission

  • Kwag, Young-Kil
    • Journal of electromagnetic engineering and science
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    • v.2 no.1
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    • pp.39-44
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    • 2002
  • A high speed data link capability is one of the critical factors in determining the performance of the spaceborne SAR system with high resolution because of the strict requirement far the real-time data transmission of the massive SAR data in a limited time of mission. In this paper, based on the data lint model characterized by the spaceborne small SAR system, the high rate multi-channel data link module is designed including link storage, link processor, transmitter, and wide-angle antenna. The design results are presented with the performance analysis on the data link budget as well as the multi-mode data rate in association with the SAR imaging mode of operation from high resolution to the wide swath.

Multi-Channel High Speed Data Link Design for Small SAR Satellite Image Data Transmission

  • Kwag, Young K.
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1436-1439
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    • 2002
  • In this paper, based on the data link model characterized by the spaceborne small SAR system, the high rate multi-channel data link module is designed including link storage, link processor, transmitter, and wide-angle antenna. The design results are presented with the performance analysis on the data link budget as well as the multi-mode data rate in association with the SAR imaging mode of operation from high resolution to the wide swath.

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Classification of Land Cover on Korean Peninsula Using Multi-temporal NOAA AVHRR Imagery

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.19 no.5
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    • pp.381-392
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    • 2003
  • Multi-temporal 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. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ~ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.

A study on aerial triangulation from multi-sensor imagery

  • Lee, Young-ran;Habib, Ayman;Kim, Kyung-Ok
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.400-406
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    • 2002
  • Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is performed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with frame imagery and vise versa. The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

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A Study on Aerial Triangulation from Multi-Sensor Imagery

  • Lee, Young-Ran;Habib, Ayman;Kim, Kyung-Ok
    • Korean Journal of Remote Sensing
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    • v.19 no.3
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    • pp.255-261
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    • 2003
  • Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is purformed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with other sensors The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

Performance of Support Vector Machine for Classifying Land Cover in Optical Satellite Images: A Case Study in Delaware River Port Area

  • Ramayanti, Suci;Kim, Bong Chan;Park, Sungjae;Lee, Chang-Wook
    • Korean Journal of Remote Sensing
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    • v.38 no.6_4
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    • pp.1911-1923
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    • 2022
  • The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

Example-based Super Resolution Text Image Reconstruction Using Image Observation Model (영상 관찰 모델을 이용한 예제기반 초해상도 텍스트 영상 복원)

  • Park, Gyu-Ro;Kim, In-Jung
    • The KIPS Transactions:PartB
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    • v.17B no.4
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    • pp.295-302
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    • 2010
  • Example-based super resolution(EBSR) is a method to reconstruct high-resolution images by learning patch-wise correspondence between high-resolution and low-resolution images. It can reconstruct a high-resolution from just a single low-resolution image. However, when it is applied to a text image whose font type and size are different from those of training images, it often produces lots of noise. The primary reason is that, in the patch matching step of the reconstruction process, input patches can be inappropriately matched to the high-resolution patches in the patch dictionary. In this paper, we propose a new patch matching method to overcome this problem. Using an image observation model, it preserves the correlation between the input and the output images. Therefore, it effectively suppresses spurious noise caused by inappropriately matched patches. This does not only improve the quality of the output image but also allows the system to use a huge dictionary containing a variety of font types and sizes, which significantly improves the adaptability to variation in font type and size. In experiments, the proposed method outperformed conventional methods in reconstruction of multi-font and multi-size images. Moreover, it improved recognition performance from 88.58% to 93.54%, which confirms the practical effect of the proposed method on recognition performance.