• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.124-127
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• 2009

In this paper, we proposed automatically video colorization method with partial color sources in first frame. The input color sources are propagated to other gray pixels with the high correlation between two pixels. To robust again the errors in portion of the weak boundary, we calculate correlation between two pixels using dual-path comparison. Video colorization method should maintain the color connectivity between frames. Accordingly, we define reliability of primarily color by compare the color of neighborhood frames. We perform the color correction by blending neighboring color when the reliability of primarily color is low. We formalize this premise with energy function, and find the color to minimize the energy function. In this way, using property of video, we reduce the error caused by propagation and get result of natural changes between frames. Through simulation results, we show the proposed method derive a natural result more than previous method.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.522-523
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• 2008

This paper presents an LED lighting which can control its color temperature. It consists of a power factor correction (PFC) circuit, an LED driver, and an LED color control circuit. The proposed system can adjusts the light intensity to obtain a desired color with independently changeable illuminance. The power factor of the PFC circuit is 98%. The LED driver has 90% efficiency at 300mA output current. The output power of the experimented LED lighting is 150 W. The achieved color temperature range was from 3000K to 7500K, and the illumination one was from 500 lux to 1500 lux.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.3-6
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• 2009

This research is an experiment to examine on the realization of Natural Color using R, G, B LEDs and this experiment was performed to cover two different stages. 1) When Natural Color using R, G, B LEDs was realized without correction in first stage, all color(R, G, B, C, M, Y) series had highly range of error from 0.0200 to 0.1500. 2) When R, G, B of LEDs was mixed at the ratio of 1:4.5907:0.0601 for realization of white in second stage, white was not realized to excitation purity. The second stage was Performed based on the three primary colors theory found out by Thomas Young in England and Hermann Ludwig Ferdinand von Helmholtz in Germany.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1702-1708
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• 2013

OLED has good efficiency of power consumption by having no power consumption from black color as different with LCD. when it has white color, all RGB pixel should be glowing with high power consumption and that can make it has short life time. This paper suggest the way of low power consumption for OLED panel using adaptive luminance enhancement with color compensation and implement it as hardware. This way which is based on luminance information of input image makes converted luminance value from each pixel in real time. There is with using the basic idea of chromaticity reduction algorithm, showing new algorithm of color correction. And performance of proposed method was confirmed by comparing the conventional method in experiments about 48.43% current reduction. The proposed method was designed by Verilog HDL and was verified by using OpenCV and Windows Program.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.16 no.1
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• pp.9-18
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• 2012

Objectives The aim of this study is to propose an optimized tongue colour interpolation method to achieve accurate tongue image rendering. Methods We selected 60 colour chips in the chips of DIC color guide selector, and then divided randomly the colour chips into two groups. The colour chips of a group (Gr I) were used for finding the optimized colour correction factor of error and those of the other group (Gr II) were used for verifying the correction factor. We measured colour value of the Gr I colour chips with spectrophotometer, and took the colour chips image with a digital tongue image system (DTIS). We adjusted colour correction factor of error to equal the chip colour from each method. Through that process, we obtained the optimized colour correction factor. To verify the correction factor, we measured colour value of the Gr II colour chips with a spectrophotometer, and took the colour chips image with the DTIS in the two types of colour interpolation mode (auto white balance mode and optimized colour correction factor mode). And then we calculated the CIE-$L^*ab$ colour difference (${\Delta}E$) between colour values measured with the spectrophotometer and those from images taken with the DTIS. Results In auto white balance mode, The mean ${\Delta}E$ between colour values measured with the spectrophotometer and those from images taken with the DTIS was 13.95. On the other hand, in optimized colour correction factor mode, The mean ${\Delta}E$ was 9.55. The correction rate was over 30%. Conclusions In case of interpolating colour of images taken with the DTIS, we suggest that procedure to search the optimized colour correction factor of error should be done first.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.173-182
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• 2013

The early Sea-viewing Wide Field-of-view Sensor(SeaWiFS) atmospheric correction algorithm which is the basis of the atmospheric correction algorithm for Geostationary Ocean Color Imager(GOCI) assumes that water-leaving radiances is negligible at near-infrared(NIR) wavelengths. For this reason, all of the satellite measured radiances at the NIR wavelengths are assigned to aerosol radiances. However that assumption would cause underestimation of water-leaving radiances if it were applied to turbid Case-2 waters. To overcome this problem, Management Unit of the North Sea Mathematical Models(MUMM) atmospheric correction algorithm has been developed for turbid waters. This MUMM algorithm introduces new parameter ${\alpha}$, representing the ratio of water-leaving reflectance at the NIR wavelengths. ${\alpha}$ is calculated by statistical method and is assumed to be constant throughout the study area. Using this algorithm, we can obtain comparatively accurate water-leaving radiances in the moderately turbid waters where the NIR water-leaving reflectance is less than approximately 0.01. However, this algorithm still underestimates the water-leaving radiances at the extremely turbid water since the ratio of water-leaving radiance at two NIR wavelengths, ${\alpha}$ is changed with concentration of suspended particles. In this study, we modified the MUMM algorithm to calculate appropriate value for ${\alpha}$ using an iterative technique. As a result, the accuracy of water-leaving reflectance has been significantly improved. Specifically, the results show that the Root Mean Square Error(RMSE) of the modified MUMM algorithm was 0.002 while that of the MUMM algorithm was 0.0048.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.11
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• pp.39-42
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• 1992

Color Doppler flow mapping (CDFM) was performed on an $\underline{in\;vitro}$ experimental setup with a regurgitant moving orifice using the proximal isovelocity surface area (PISA) technique. PISA flow rates underestimated actual flow rates by as much as 65%, which is very important in diagnosing patients with valvular regurgitations or stenosis. The correction factor considering the velocity of the orifice improved the PISA flow rates.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.289-305
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• 2004

Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.535-546
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• 2010

Digital images have undesired color casts due to various illumination conditions and intrinsic characteristics of cameras. Since the color casts in the images deteriorate performance of color representations, color correction is required for further analysis of images. In this paper, an algorithm for detection and removal of color casts is presented. The proposed algorithm consists of four steps: retrieving similar image using color by correlation, extraction of near neutral color regions, kernel density estimation, and removal of color casts. Ambiguities in near neutral color regions are excluded based on kernel density estimation by the color by correlation algorithm. The method determines whether there are color casts by chromaticity distributions in near neutral color regions, and removes color casts for color constancy. Experimental results suggest that the proposed method outperforms the gray world algorithm and the color by correlation algorithm.