• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.822-832
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• 1994

DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Journal of Sensor Science and Technology
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• v.7 no.6
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• pp.394-400
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• 1998

In this paper, we present a robust and fast method that enables real-time computing of axial motion component of different points of a scene from a stereo images sequence. The aim of our method is to establish axial motion maps by computing a range of disparity maps. We propose a solution in two steps. In the first step we estimate motion with a low level computing for an image point by a detection estimation-structure. In the second step, we use the neighbourhood information of the image point with morphology operation. The motion maps are established with a constant computation time without spatio-temporal matching.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.171-176
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• 1998

This paper resents a spatio-temporal video segmentation method. The algorithm segments each frame of video sequences captured by a static or moving camera into moving objects (foreground) and background using a statistical hypothesis test. In the proposed method, three consecutive image frames are exploited and a hypothesis testing is performed by comparing two means from two consecutive difference images, which results in a T-test. This hypothesis test yields change detection mask that indicates moving areas (foreground) and non-moving areas (background). Moreover, an effective method for extracting object mask form change detection mask is proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.217-221
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• 2002

In this paper, we propose a new scheme of motion tracking based on fuzzy inference (FI)and wavelet transform (WT) from image sequences. First, we present a WT to segment a feature extraction of dynamic image . The coefficient matrix for 2-level DWT tent to be clustered around the location of important features in the images, such as edge discontinuities, peaks, and corners. But these features are time varying owing to the environment conditions. Second, to reduce the spatio-temporal error, We develop a fuzzy inference algorithm. Some experiments are peformed to testify the validity and applicability of the proposed system. As a result, proposed method is relatively simple compared with the traditional space domain method. It is also well suited for motion tracking under the conditions of variation of illumination.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.155-163
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• 2009

An abundance of internal waves is observed by SAR in the Yellow Sea during summer. They are small scaled internal waves and are not relatively studied well compared to the ones in the East/South China Sea. These internal waves should be considered in the study of physio-biological properties of the Yellow Sea because the mixing of the stratified surface water caused by internal waves during summer is important for ocean biological environment, and they also affect the sediment transport and acoustic signal transmission in the continental shelf region. To understand the characteristics of internal waves, it is important to get the spatio-temporal information of internal waves simultaneously by executing in-situ measurements as well as the SAR observation. This study tracks the internal waves observed by SAR in the time series of temperature profile data by analyzing simultaneously acquired in-situ measurement data and RADARSAT SAR image on 29 May 2002.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.15-15
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• 2022

우리나라 홍수 발생은 강수량이 집중되는 여름철에 집중되어 있어 홍수피해 방지에 주의가 필요하다. 보와 제방 등 이러한 홍수 피해를 대비하기 위한 구조물에 설계를 위해서는 하천의 유량 조사가 필수적으로 요구된다. 하지만 홍수기 직접적인 유량 조사는 안전상의 이유로 거의 이루어지지지 않고 있으며, 수위를 측정하여 수위-유량 관계를 만들어 유량을 측정하고 있다. 그러나 중소 규모의 하천의 경우 하도 경사가 급해 사류가 발생하거나 하도 단면이 급변하는 경우가 있어 수위-유량 관계를 그대로 적용하기 어려운 문제가 있다. 따라서 이러한 문제를 해결하기 위해 하천에 진입하지 않고 유속을 측정 할 수 있는 영상유속계와 같이 흐름 영상을 사용하여 유속을 측정하는 방법들이 개발되었다. 영상유속계의 측정 방법중 Spatio Temporal Image(시공간 영상)을 사용하는 방법은 일정시간의 시간평균 유속을 산정할 수 있고 한 장의 시공간 영상을 분석하기 때문에 유속 산정에 걸리는 시간이 작은 장점이 있지만 영상 내 흐름 방향을 정확히 설정하지 못하면 오차가 생길 수 있는 문제가 있어 주 흐름 방향을 정확히 탐색할 필요가 있다. 따라서 본 연구에서는 영상에서 시공간 체적을 만들어 주흐름 방향을 찾아내는 기법들의 장단점을 비교하고 안동 하천실험센터의 실규모 하천수로에 적용하여 결과를 비교하고 적용성을 평가하였다. 이를 위해 하천수로에 추적자를 살포하여 영상으로 녹화하였으며 녹화된 영상을 자기상관법과 시간적분법을 적용하였으며, 이를 통해 주 흐름 방향을 판별하였다. 또한 두 방법을 통해 결정된 주흐름 방향을 적용하여 시공간 영상을 제작하고 이를 이용하여 유속을 산정하여 비교하였으며, 주흐름 방향을 산정하는데 생기는 오차가 유속 계산에 얼마만큼의 영향을 끼치는지 분석하였다. 이러한 실험을 통해 하천에서 시공간 영상을 활용한 표면영상 유속계측 방법을 활용하는데 있어 도움이 될 것으로 기대된다.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.765-790
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• 2021

The affection-image is the close-up of the face with real connections in space-time, or with virtual conjunction, outside spatio-temporal co-ordinates. The close-up can carry its own space-time in background. with deframing and fragmentation, Space itself has left behind its own space-time connection and become any-space-whatever that is the affection-image. The elements of any-space-whatever are the shadows, lyrical abstraction, the colors, the disconnected parts, the empty space. Deleuze examines any-space-whatever through the close ups, fragmentation of space and de-framing in Dreyer and Bresson's cinema.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.119-125
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• 2017

The mud flat in Korea is the geographical feature generated from the sediment of rivers of Korea and China and it is the important topography for pollution purification and fishing industry. The mud flat is difficult to access such that it requires the aerial survey for the high-resolution spatial information of the area. In this study we used drones instead of the conventional aerial and remote sensing approaches which have shortcomings of costs and revisit times. We carried out GPS-based control point survey, temporal image acquisition using drones, bundle adjustment, stereo image processing for DSM and ortho photo generation, followed by co-registration between the spatio-temporal information.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.517-534
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• 2019

In abrupt fire disturbances, high quality images suitable for wildfire damage assessment can be difficult to acquire. Quantifying wildfire burn area and severity are essential measures for quick short-term disaster response and efficient long-term disaster restoration. Planetscope (PS) imagery offers 3 m spatial and daily temporal resolution, which can overcome the spatio-temporal resolution tradeoff of conventional satellites, albeit at the cost of spectral resolution. This study investigated the potential of augmenting PS imagery by integrating the spectral information from Sentinel-2 (S2) differenced Normalized Burn Ratio (dNBR) to PS differenced Normalized Difference Vegetation Index (dNDVI) using histogram matching,specifically for wildfire burn area and severity assessment of the Okgye wildfire which occurred on April 4th, 2019. Due to the difficulty in acquiring reference data, the results of the study were compared to the wildfire burn area reported by Ministry of the Interior and Safety. The burn area estimates from this study demonstrated that the histogram-matched (HM) PS dNDVI image produced more accurate burn area estimates and more descriptive burn severity intervals in contrast to conventional methods using S2. The HM PS dNDVI image returned an error of only 0.691% whereas the S2 dNDVI and dNBR images overestimated the wildfire burn area by 5.32% and 106%, respectively. These improvements using PS were largely due to the higher spatial resolution, allowing for the detection of sparsely distributed patches of land and narrow roads, which were indistinguishable using S2 dNBR. In addition, the integration of spectral information from S2 in the PS image resolved saturation effects in areas of low and high burn severity.