• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.481-483
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• 2004

다양한 동영상 압축표준에서 압축효율을 높이기 위해 1/2 화소를 이용한다. 1/2 화소는 프레임 간 참조시 압축 효율을 높이기 위한 프레임 내 화소를 연산하여 생성되는 가상의 값이며 이 연산식은 표준에 따라 다르다. MPEG-2에서 H.264로의 포맷 변환시 이 1/2 화소값의 차이로 인해 MPEG-2의 모션벡터와 움직임 보상된 값을 그대로 사용할 수 없게 된다. 본 논문에서는 MPEG-2의 모션벡터를 그대로 사용하고 DCT(Discrete Cosine Transform) 도메인에서 두 표준의 화소값의 차이를 보정하는 기법을 제안한다. 제안된 기법은 픽셀 도메인의 창조 블록을 이용하여 보정 할 위치를 찾고 두 표준의 1/2 화소 계산식의 차이를 이용하여 보정 할 값을 구하게 된다. 구해진 보정 값을 DCT하여 DCT 도메인의 현재 블록에 더하여 보정하게 된다. 이 기법은 모든 블록의 값을 완벽하게 보정할 수는 없지만 두 표준 간 차이값이 큰 1/2 화소를 보정할 수 있으며 IDCT라 DCT로 인한 화질 열화도 감소된다 또한, DCT 상태에서 보정을 수행하므로 픽셀 도메인에서 보다 약 7%의 계산복잡도도 낮출 수 있다.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.956-962
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• 2005

To improve video quality and coding efficiency, H.264/AVC adopts different half pixel calculating method compared with the previous standards. So, the transcoder requires additional works to transcode the pre-coded video contents with the previous standards to H.264/AVC in DCT domain. In this paper, we propose the first half-pixel correction method for MPEG-2 to H.264 transcoding in DCT domain. In the proposed method, MPEG-2 block is added to the correction block obtained by difference calculation of half-pixel values between two standards using DCT reference frame. Experimental results show that the proposed achieves better quality than pixel based cascaded transcoding method.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.364-366
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• 2005

최신 동영상 압축 표준인 H.264는 압축 효율을 높이기 위해 기존의 표준과는 다른 1/2 화소 생성 방법을 사용한다. 그러므로 기존의 동영상 압축표준으로 압축된 비트열을 DCT 상에서 H.264로 트랜스코딩(transcoding)하기 위해서는 추가적인 보정 작업이 필요하다. 본 논문에서는 MPEG-2로 압축된 비트열을 DCT 상에서 H.264로 트랜스코딩 할 때 두 표준 간 1/2 화소 값의 차이를 보정하는 기법을 제안한다. 제안된 1/2 화소 보정 기법에서는 DCT 상태의 창조 프레임을 이용하여 두 표준 간의 차이 값을 구하여 입력으로 들어온 블록의 값에 더하여 보정한다. 픽셀 기반에서 보정하는 기법과 성능을 비교한 결과 제안하는 기법이 화질 면에서 우수하며 움직임이 빠른 비디오의 경우 계산량이 높아지는 것으로 나타났다.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.189-198
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• 2022

In this present study, we investigated the effect of the offset correction factor calculation method on the sulfur dioxide (SO₂) column density in the SO₂ retrieval algorithm of the Geostationary Environment Monitoring Spectrometer (GEMS) launched in February 2020. The GEMS operational SO₂ retrieval algorithm is the Differential Optical Absorption Spectroscopy (DOAS) - Principal Component Analysis (PCA) Hybrid algorithm. In the GEMS Hybrid algorithm, the offset correction process is essential to correct the absorption effect of ozone appearing in the SO₂ slant column density (SCD) obtained after spectral fitting using DOAS. Since the SO₂ column density may depend on the conditions for calculating the offset correction factor, it is necessary to apply an appropriate offset correction value. In this present study, the offset correction values were calculated for days with many cloud pixels and few cloud pixels, respectively. And a comparison of the SO₂ column density retrieved by applying each offset correction factor to the GEMS operational SO₂ retrieval algorithm was performed. When the offset correction value was calculated using radiance data of GEMS on a day with many cloud pixels was used, the standard deviation of the SO₂ column density around India and the Korean Peninsula, which are the edges of the GEMS observation area, was 1.27 DU, and 0.58 DU, respectively. And around Hong Kong, where there were many cloud pixels, the SO₂ standard deviation was 0.77 DU. On the other hand, when the offset correction value calculated using the GEMS data on the day with few cloud pixels was used, the standard deviation of the SO₂ column density slightly decreased around India (0.72 DU), Korean Peninsula (0.38 DU), and Hong Kong (0.44 DU). We found that the SO₂ retrieval was relatively stable compared to the SO₂ retrieval case using the offset correction value on the day with many cloud pixels. Accordingly, to minimize the uncertainty of the GEMS SO₂ retrieval algorithm and to obtain a stable retrieval, it is necessary to calculate the offset correction factor under appropriate conditions.

• Journal of Convergence Society for SMB
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• v.6 no.3
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• pp.85-91
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• 2016

It was difficult to verify the car number or face of inspector in the closed circuit television because of low CCD pixels and low brightness of lens. So CCTV lens should have higher pixels and brightness. In this paper, the design of zoom lens for mega pixel Closed-Circuit Television (CCTV) was introduced. We applied aspheric lens in order to reduce the spherical aberration and distortional aberration. And we applied focal length of 6-60mm, F number of 1.2, 3 million pixel resolution and magnifying power of 10 times. Also we applied infrared correction in order to use the CCTV camera in day and night effectively. These norms are the most powerful in CCTV zoom lens of focal length of 6-60mm. And if we apply this lens to the box style CCTV camera, we can verify the car number or face within 50m. Auto controlling system will be continued.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.51-64
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• 2015

We improved the MODerate resolution Imaging Spectroradiometer (MODIS) land cover map over the Asia-Oceania region through the reclassification of the misclassified pixels. The misclassified pixels are defined where the number of land cover types are greater than 3 from the 12 years of MODIS land cover map. The ratio of misclassified pixels in this region amounts to 17.53%. The MODIS Normalized Difference Vegetation Index (NDVI) time series over the correctly classified pixels showed that continuous variation with time without noises. However, there are so many unreasonable fluctuations in the NDVI time series for the misclassified pixels. To improve the quality of input data for the reclassification, we corrected the MODIS NDVI using Correction based on Spatial and Temporal Continuity (CSaTC) developed by Cho and Suh (2013). Iterative Self-Organizing Data Analysis (ISODATA) was used for the clustering of NDVI data over the misclassified pixels and land cover types was determined based on the seasonal variation pattern of NDVI. The final land cover map was generated through the merging of correctly classified MODIS land cover map and reclassified land cover map. The validation results using the 138 ground truth data showed that the overall accuracy of classification is improved from 68% of original MODIS land cover map to 74% of reclassified land cover map.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1143-1153
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• 2018

For TOPS InSAR processing, high-precision image co-registration is required. We propose an image co-registration method suitable for the TOPS mode by comparing the performance of cross correlation method, the geometric co-registration and the enhanced spectral diversity (ESD) matching algorithm based on the spectral diversity (SD) on the Sentinel-1 TOPS mode image. Using 23 pairs of interferometric pairs generated from 25 Sentinel-1 TOPS images, we applied the cross correlation (CC), geometric correction with only orbit information (GC1), geometric correction combined with iterative cross-correlation (GC2, GC3, GC4), and ESD iteration (ESD_GC, ESD_1, ESD_2). The mean of co-registration errors in azimuth direction by cross correlation and geometric matching are 0.0041 pixels and 0.0016 pixels, respectively. Although the ESD method shows the most accurate result with the error of less than 0.0005 pixels, the error of geometric co-registration is reduced to 0.001 pixels by repetition through additional cross correlation matching between the reference and resampled slave image. The ESD method is not applicable when the coherence of the burst overlap areas is low. Therefore, the geometric co-registration method through iterative processing is a suitable alternative for time series analysis using multiple SAR data or generating interferogram with long time intervals.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1149-1160
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• 2019

In this study, two radiometric correction methods deriving reflectance from UAV multispectral image for monitoring forest vegetation were applied and evaluated. Multispectral images were obtained from a small multispectral camera having 5 spectral bands. Reflectance were derived by applying the two methods: (1) the direct method using downwelling irradiance measurement and (2) the empirical line correction method by linking a set of field reflectance measured simultaneous with the image capture. Field reflectance were obtained using a spectroradiometer during the flight and used for building the linear equation for the empirical method and for the validation of image reflectance derived. Although both methods provided the high correlations between field reflectance and image-derived reflectance, their distributions were somewhat different. While the direct method provided rather stable and consistent distribution of reflectance all over the entire image area, the empirical method showed very unstable and inconsistent reflectance distribution. The direct method would be more appropriate for relatively wide area that requires more time to acquire image and may vary in downwelling irradiance and atmospheric conditions.

• Journal of the Korean Society of Radiology
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• v.13 no.7
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• pp.925-932
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• 2019

In this paper, we developed optical dosimetry system with a plastic scintillator, a commercial 50 mm, f1.8 lens, and a commercial high-sensitivity CMOS (complementary metal-oxide semiconductor) camera. And, the correction processors of vignetting, geometrical distortion and scaling were established. Using the developed system, we can measured a percent depth dose, a beam profile and a dose linearity for 6 MV medical LINAC (Linear Accelerator). As results, the optically measured percent depth dose was well matched with the measured percent depth dose by ion-chamber within 2% tolerance. And the determined flatness was 2.8%. We concluded that the optical dosimetry system was sufficient for application of absorbed dose monitoring during radiation therapy.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1301-1314
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• 2022

Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.