• Title/Summary/Keyword: 신호 채움

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Efficient Signal Filling Method Using Watershed Algorithm for MRC-based Image Compression (MRC 기반의 영상 부호화를 위한 분수령 알고리즘을 이용한 효과적인 신호 채움 기법)

  • Park, Sang-Hyo;Lee, Si-Woong
    • The Journal of the Korea Contents Association
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    • v.15 no.2
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    • pp.21-30
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    • 2015
  • Image coding based on mixed raster content model generates don't care regions (DCR) in foreground and background layers, and its overall coding performance is greatly affected by region filling methods for DCRs. Most conventional methods for DCR filling fail in utilizing the local signal properties in hole regions and thus the high frequency components in non-DCR regions are reflected into DCR after signal filling. In addition, further high frequency components are induced to the filled signal because of signal discontinuities in the boundary of DCR. To solve this problem, a new DCR filling algorithm using the priority-based adaptive region growing is proposed in this paper. The proposed method uses the watershed algorithm and the flooding priority of each pixel for region filling is determined from the degree of smoothness in the neighborhood area. By growing the filled region into DCR based on the computed priority, the expansion of high-textured area can be minimized which can improve the overall coding performance. Experimental results show that the proposed method outperforms conventional algorithms.

Estimation of Groundwater Table using Ground Penetration Radar (GPR) in a Sand Tank Model and at an Alluvial Field Site (실내 모형과 현장 충적층에서 지하투과레이더를 이용한 지하수면 추정)

  • Kim, Byung-Woo;Kim, Hyoung-Soo;Choi, Doo-Houng;Koh, Yong-Kwon
    • The Journal of Engineering Geology
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    • v.23 no.3
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    • pp.201-216
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    • 2013
  • Ground penetrating radar (GPR) surveys were conducted in a sand tank model in a laboratory and at an alluvial field site to detect the groundwater table and to investigate the influence of saturation on GPR response in the unsaturated zone. In the sand tank model, the groundwater table and saturation in the sand layer were altered by injecting water, which was then drained by a valve inserted into the bottom of the tank. GPR vertical reflection profile (VRP) data were obtained in the sand tank model for rising and lowering of the groundwater table to estimate the groundwater table and saturation. Results of the lab-scale model provide information on the sensitivity of GPR signals to changes in the water content and in the groundwater table. GPR wave velocities in the vadose zone are controlled mainly by variations in water content (increased travel time is interpreted as an increase in saturation). At the field site, VRP data were collected to a depth of 220 m to estimate the groundwater table at an alluvial site near the Nakdong river at Iryong-ri, Haman-gun, South Korea. Results of the field survey indicate that under saturated conditions, the first reflector of the GPR is indicative of the capillary fringe and not the actual groundwater table. To measure the groundwater table more accurately, we performed a GPR survey using the common mid-point (CMP) method in the vicinity of well-3, and sunk a well to check the groundwater table. The resultant CMP data revealed reflective events from the capillary fringe and groundwater table showing hyperbolic patterns. The normal moveout correction was applied to evaluate the velocity of the GPR, which improved the accuracy of saturation and groundwater table information at depth. The GPR results show that the saturation information, including the groundwater table, is useful in assessing the hydrogeologic properties of the vadose zone in the field.

Image Processing of GPR Detection Data (GPR 탐사 데이터의 이미지 처리)

  • Lee, Hyun-Ho
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.20 no.4
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    • pp.104-110
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    • 2016
  • To get the empirical data of GPR detection and to develop the image prosessing program of GPR detection data, GPR detection were proceed by the underground pipes and cavities buried in the Chamber. In the case of non pavement and asphalt pavement, water filled cavity that was buried in 0.7m depth was able to detection. But in the case of 1.0 m and 1.3 m buring depth, water filled cavity was not able to detection. In the case of non-reinforced and reinforced concrete pavement, it was difficult to detect the cavity caused by signal interference. GPRiPP programs was developed for image processing of the GPR detection data. The major processing algorithm were background removal, stacking and gain function. With proper image processing of gain function and background removal in GPRiPP program, it was showed that similar results can be obtained with conventional image processing program.