• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.345-348
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• 1997

Endoscope image is the shape that a doctor sees inside of patient through endoscope. The characteristics of these images are much effected by the light source of endoscope, specially areas in short distance from a light have much light source and look clear, but areas in long distance from a light look dark relatively because of little light quantity. So we developed a new level adaptive image enhancer for the dark area in a endoscope image. The algorithm we made consists of three parts ; 1) Classification of histogram in segmented area 2) Smoothing and Adaptive Histogram Equalization 3) Adaptive Histogram Modification.

• Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.1-15
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• 2015

Measured bidirectional reflectance distribution function (BRDF) data have been used to represent complex interaction between lights and surface materials for photorealistic rendering. However, their massive size makes it hard to adopt them in practical rendering applications. In this paper, we propose an adaptive method for B-spline volume representation of measured BRDF data. It basically performs approximate B-spline volume lofting, which decomposes the problem into three sub-problems of multiple B-spline curve fitting along u-, v-, and w-parametric directions. Especially, it makes the efficient use of knots in the multiple B-spline curve fitting and thereby accomplishes adaptive knot placement along each parametric direction of a resulting B-spline volume. The proposed method is quite useful to realize efficient data reduction while smoothing out the noises and keeping the overall features of BRDF data well. By applying the B-spline volume models of real materials for rendering, we show that the B-spline volume models are effective in preserving the features of material appearance and are suitable for representing BRDF data.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.471-482
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• 2006

In this paper, we propose a new scheme to generate multi-view images utilizing depth map decomposition and adaptive edge smoothing. After carrying out smooth filtering based on an adaptive window size to regions of edges in the depth map, we decompose the smoothed depth map into four types of images: regular mesh, object boundary, feature point, and number-of-layer images. Then, we generate 3-D scenes from the decomposed images using a 3-D mesh triangulation technique. Finally, we extract multi-view images from the reconstructed 3-D scenes by changing the position of a virtual camera in the 3-D space. Experimental results show that our scheme generates multi-view images successfully by minimizing a rubber-sheet problem using edge smoothing, and renders consecutive 3-D scenes in real time through information decomposition of depth maps. In addition, the proposed scheme can be used for 3-D applications that need the depth information, such as depth keying, since we can preserve the depth data unlike the previous unsymmetric filtering method.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.615-619
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• 2009

A real-time, continuous-scale image interpolation method is proposed based on bi-linear interpolation with directionally adaptive low-pass filtering. The proposed algorithm has been optimized for hardware implementation. The original bi-linear interpolation method has blocking artifact. The proposed algorithm solves this problem using directionally adaptive low-pass filtering. It can also solve the severely problem by selection choosing low-pass filter coefficients. Therefore the proposed interpolation algorithm can realize a high-quality image scaler for various imaging systems, such as digital camera, CCTV and digital flat panel display, to name a few.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.41-47
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• 2022

Smoothing is a transmission plan that converts video data stored at a variable bit rate into a fixed bit rate. Algorithms for smoothing include CBA, which aims to minimize the number of transmission rate increases, MCBA, which minimizes the number of transmission rate changes, and MVBA algorithms that minimize the amount of transmission rate change. This paper compares the proposed algorithm with the CBA algorithm with various video data, buffer size, and performance evaluation factors as a follow-up to the proposed smoothing algorithm that minimizes (maximizes) the transmission rate increase (decrease) when the server requires more bandwidth The evaluation factors used were compared with the number of changes in the fps rate, the minimum fps, the average fps, fps variability, and the number of frames to be discarded. As a result of the comparison, the proposed algorithm showed superiority in comparing the number of fps rate changes and the number of frames discarded.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.11-17
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• 2023

Smoothing is to creating a transmission plan consisting of sections of frames that can be sent at the same transmission rate for compressed and stored video data. Various algorithms have been studied for the smoothing to minimize the number of transmission rate changes, the number of transmission rate changes, and the amount of transmission rate increase. This study evaluates the performance of a smoothing algorithm that minimizes the increase in transmission rates and maximizes the increase in transmission rates when the transmission rate is required to maximize the excess bandwidth to be secured by the server in an environment with limited server bandwidth. The available transmission rates and buffer sizes available in the server are set in various ways and evaluated by the number of fps changes, the minimum fps, the average fps, and fps variability. As a result of the comparison, the proposed algorithm showed excellent average fps and fps variability.

• Journal of the Korea Computer Graphics Society
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• v.23 no.4
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• pp.11-19
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• 2017

We propose a new pipeline of fluid surface reconstruction that incorporates hybrid SDF(signed distance fields) and adaptive fluid surface techniques to finely reconstruct liquid-solid mixed surfaces. Previous particle-based fluid simulation suffer from a noisy surface problem when the particles are distributed irregularly. If a smoothing scheme is applied to reduce the problem, sharp and detailed features can be lost by over-smoothing artifacts. Our method constructs a hybrid SDF by combining signed distance values from the solid and liquid parts of the object. We also proposed a method of adaptively reconstructing the surface of the fluid to further improve the overall efficiency. This not only shows the detailed surface of the solid and liquid parts, but also the detail of the solid surface and the smooth fluid surface when both materials are mixed. We introduce the concept of guiding shape and propose a method to get signed distance value quickly. In addition, the hybrid SDF and mesh reconstruction techniques are integrated in the adaptive framework. As a result, our method improves the overall efficiency of the pipeline to restore fluid surfaces.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.8
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• pp.1-7
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• 2005

This paper proposes a local improvement method that combines extended topological clean up and optimization-based smoothing for homogenizing triangular grid system. First extended topological clean up procedures are applied to improve the connectivities of grid elements. Then, local optimization-based smoothing is performed for maximizing the distortion metric that measures grid quality. Using the local improvement strategy, we implement the grid homogenizations for two triangular grid examples. It is shown that the suggested algorithm improves the quality of the triangular grids to a great degree in an efficient manner and also can be easily applied to the remeshing algorithm in adaptive mesh refinement technique.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.113-123
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• 1996

Data-dependent (adaptive) choice of asymptotically efficient score functions for rank estimators and M-estimators of regression parameters in a linear regression model with left-truncated and right-censored data are developed herein. The locally adaptive smoothing techniques of Muller and Wang (1990) and Uzunogullari and Wang (1992) provide good estimates of the hazard function h and its derivative h' from left-truncated and right-censored data. However, since we need to estimate h'/h for the asymptotically optimal choice of score functions, the naive estimator, which is just a ratio of estimated h' and h, turns out to have a few drawbacks. An altermative method to overcome these shortcomings and also to speed up the algorithms is developed. In particular, we use a subroutine of the PPR (Projection Pursuit Regression) method coded by Friedman and Stuetzle (1981) to find the nonparametric derivative of log(h) for the problem of estimating h'/h.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1711-1714
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• 2003

The noise in an image degrades image quality and deteriorates coding efficiency of compression. Recently, various edge-preserving noise filtering methods based on the nonstationary image model have been proposed to overcome this problem. In most conventional nonstationary image models, however, pixels are assumed to be uncorrelated to each other In order not to increase the computational burden too much. As a result, some detailed information is lost in the filtered results. In this paper, we propose a computationally feasible adaptive noise smoothing algorithm which considers the nonstationary correlation characteristics of images. We assume that an image has a nonstationary mean and can be segmented into subimages which have individually different stationary correlations. Taking advantage of the special structure of the covariance matrix that results from the proposed image model, we derive a computationally efficient FFT-based adaptive linear minimum mean square error filter. The justification for the proposed image model is presented and the effectiveness of the proposed algorithm is demonstrated experimentally.