• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.268-273
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• 1998

This study applies an on-line system, which employes an adaptive reconstruction technique to monitor and forecast ocean surface changes. The system adaptively generates an appropriate synthetic time series with recovering missing measurements for sequential images. The reconstruction method incorporates temporal variation according to physical properties of targets and anisotropic spatial optical properties into image processing techniques. This adaptive approach allows successive refinement of the structure of objects that are barely detectable in the observed series. The system sequentially collects the estimated results from the adaptive reconstruction and then statistically analyzes them to monitor and forecast the change in surface characteristics.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.57-60
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• 2000

This paper presents a new adaptive fast motion estimation algorithm along with its architecture. The conventional algorithm such as full - search algorithm, three step algorithm have some disadvantages which are related to the amount of computation, the quality of image and the implementation of hardware, the proposed algorithm uses spatial correlation and a slope of motion vector in order to reduce the amount of computation and preserve good image quality, The proposed algorithm is better than the conventional Block Matching Algorithm(BMA) with regard to the amount of computation and image quality. Also, we propose an efficient at chitecture to implement the proposed algorithm. It is suitable for real time processing application.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.146-156
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• 2002

This paper presents an adaptive H.263+ rate control algorithm for streaming video applications under the networks supporting bandwidth renegotiation, which can communicate with end-users to accommodate their time-varying bandwidth requests during the data transmission. That is, the requests of end-users can be supported adaptively according to the availability of the network resources, and thus the overall network utilization can be improved simultaneously. They are especially suitable for the transmission of non-stationary video traffics. The proposed rate control algorithm communicates with the network to renegotiate the required bandwidth fort the underlying video which are measured based on the motion change information, and choose their control strategies according to the renegotiation results. Unlike most conventional algorithms that control only the spatial quality by adjusting quantization parameters, the proposed algorithm treats both the spatial and temporal qualities at the same time to enhance human visual perceptual quality. Experimental results are provided to demonstrate that the proposed rate control algorithm can achieve superior performance to the conventional ones with low computational complexity under the networks supporting bandwidth renegotiation.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.152-159
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• 1997

The asymptotic convergence of a coupled dynamic system, which is motivated from infinite dimensional adaptive systems, is investigated. The convergence analysis is formulated in abstract Banch spaces and is shown to applicable to a broad class of infinite dimensional systems including adaptive identification and adaptive control. Particularly it is shown that if a uniquely existing solution is p-th power integrable, then the solution converges to zero asymptotically. The persistence of excitation(PE) of a signal which arises in an infinite dimensional adaptive system is investigated. The PE property is not completely known yet for infinite dimensional adaptive systems, however it should be investigated in relation to spatial variable, boundary conditions as well as time variable.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.145-159
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• 1996

We propose an adaptive searching method using some spatial relations among sample points to estimate the interesting area in the spatial population. The fundamental idea is to observe the neighboring sample points when a sample point is satified with some condition of an adaptive searching observation. For obseving the sample points with this method to estimate the area the sample size is decreased. From this result, we may expect to reduce the cost and time consuming in observation the sample points and to draw the shape of the interesting area without prior information of an spatial population. Some analytical simulation results are also presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7A
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• pp.568-577
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• 2005

In this paper, we propose the transmission scheme for the space-time block coded spatial multiplexing systems that have adaptive rate and power allocation per each transmit antenna through the use of feedback information related to channel state. Simulation results show that the adaptive power and rate transmission scheme gain more than 4.5 dB over conventional equal-power and rate transmission scheme.

• Journal of IKEEE
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• v.27 no.1
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• pp.38-44
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• 2023

Performance of a STAP(space-time adaptive processing) algorithm highly depends on how closely the estimated covariance matrix(CM) resembles the actual CM by the interference in CUT(cell under test). A STAP has 2 dimensional data structure determined by the number of array elements and the number of transmitting pulses and both numbers are generally not small. Thus, to meet the degree of freedom(DOF) of the CM, a huge amount of training data is required. This paper presents an algorithm to generate virtual training data from small received data, via converting them into the data in spatial frequency-Doppler plane. We theoretically derive where the clutter exist in the plane and present the procedure to implement the proposed algorithm. Finally, with the simulated scenario of small received data, we show the proposed algorithm can improve STAP performance.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1209-1219
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• 2019

For consistent vegetation monitoring, it is necessary to generate time-series vegetation index datasets at fine temporal and spatial scales by fusing the complementary characteristics between temporal and spatial scales of multiple satellite data. In this study, we quantitatively and qualitatively analyzed the prediction accuracy of time-series change information extracted from spatio-temporal fusion models of multiple satellite data for vegetation monitoring. As for the spatio-temporal fusion models, we applied two models that have been widely employed to vegetation monitoring, including a Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). To quantitatively evaluate the prediction accuracy, we first generated simulated data sets from MODIS data with fine temporal scales and then used them as inputs for the spatio-temporal fusion models. We observed from the comparative experiment that ESTARFM showed better prediction performance than STARFM, but the prediction performance for the two models became degraded as the difference between the prediction date and the simultaneous acquisition date of the input data increased. This result indicates that multiple data acquired close to the prediction date should be used to improve the prediction accuracy. When considering the limited availability of optical images, it is necessary to develop an advanced spatio-temporal model that can reflect the suggestions of this study for vegetation monitoring.

• Journal of computational fluids engineering
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• v.13 no.3
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• pp.69-78
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• 2008

The high-order numerical method based on the adaptive mesh refinement(AMR) on the quadrilateral unstructured grids has been developed in this paper. This adaptive-grid method, originally developed with MUSCL-TVD scheme, is now extended to the WENO (weighted essentially no-oscillatory) scheme with the Runge-Kutta time integration of fifth order in spatial and temporal accuracy. The multidimensional interpolation was studied in the preliminary research, which allows us to maintain the same order of accuracy for the computation of numerical flux between two adjacent cells of different levels. Some standard benchmark tests are done to validate this method for checking the overall capacity and efficiency of the present adaptive-grid technique.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.45-51
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• 2002

The goal of image merging techniques are to enhance the resolution of low-resolution images using the detail information of the high-resolution images. Among the several image merging methods, wavelet-based image merging techniques have the advantages of efficient decorrelation of image bands and time-scale analysis. However, they have no regard for spatial information between the bands. In other words, multiresolution data merging methods merge the same information-the detail information of panchromatic image-with other band images, without considering specific characteristics. Therefore, a merged image contains much unnecessary information. In this paper, we discussed this 'mixing' effect and, proposed a method to classify the detail information of the panchromatic image according to the spatial and spectral characteristics, and to minimize distortion of the merged image.