• Spatial Information Research
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• v.3 no.1
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• pp.19-27
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• 1995

In this paper, a semi-automated mapping system, which can produ¬ce digital maps by using information acquired from pre-processing procedure, was introduced. To get a binary edge image, which is very important in vectori¬zation process, we applied adaptive smoothing and connection preserving thresho¬Iding algorithm. In mapper program, binary images are converted to vectors and for in-core data structure, extended PR quad tree was used. These procedures are dispatched to personal computers and workstations and through network resource sharing, the whole process was unified and simplified.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1685-1692
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• 2010

The Laplacian operator is usually used as a regularization operator which may be used as any differential operator in the regularization iterative processing. In this paper, several kinds of differential operator and proposed operator as a regularization operator were compared with each other performance. For noisy gaussian-blurred images, proposed operator worked better in the edge, while in flat region the conventional operator resulted better. In regularization, smoothing the noise and restoring the edges should be considered at the same time, so the regions divided into the flat, the middle, and the detailed, which were processed in separate and compared.

• Journal of Biomedical Engineering Research
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• v.19 no.6
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• pp.551-562
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• 1998

Amultiresolution filtering algorithm based on the physical SPECT lesion detachability provides and optimal solution for SPECT reconstruction problem. Related to the previous study, we estimated the SPECT lesion detection capability by m minimum detectable lesion sizes (MDLSs), and generated m reconstruction filters which are designed to maximize the smoothing effect at a fixed MDLS-dependent resolution level $\frac{MDLS}{4\sqrt{2In2}}$. The proposed multiresolution filtering algorithm used a coarse-to-fine approach for the m-level resolution filter images obtained from these m filters for a given projection image. First, the local homogeneity is determined for every pixel of the filter images, by comparing the local variance value computed in a window centered at the pixel and the mode determined from the distribution of the local variances. Based on the local homogeneity, the pixels declared as homogeneous are chosen from the filter image of the lowest resolution, and for the other pixels the same process is repeated for the higher resolution filter images. For the non-homogeneous pixels after this pixels after this repetition process ends, the pixel values of the highest resolution filter image are substituted. From the results of the simulated experiments, the proposed multiresolution filtering algorithm showed a strong smoothing effect in the homogeneous regions and a significant resolution improvement near the edge regions of the projection images, and so produced good adaptability effects in the reconstructed images.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.56-63
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• 2012

In this paper, adaptive unsharp masking using bilateral filter, edge-preserving smoothing filter is proposed to reduce the overshoot and jagging artifact in sharpening images. Previous image enhancement methods including unsharp masking(UM) can emphasize high-frequency details strongly, but often cause several artifacts such as overshooting, noise, jagging and so on. Proposed image enhancement method preserves edges well because of using bilateral filter and sensitively controls a weight according to edge's directions. Therefore, it enhances sharpness and effectively reduces overshoot and jagging artifacts. Simulation results comparing output of previous AUM with proposed method show that proposed algorithm makes images properly enhanced, and we know that overshoot and jagging artifacts are many reduced.

• Journal of the Korean Society of Radiology
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• v.2 no.1
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• pp.23-29
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• 2008

The present study proposed a method that dissolves ultrasonographic images into multiple resolutions using wavelet conversion and a boundary detection filter and improves the quality of ultrasonographic images through boundary detection filtering. In order to reduce noises and strengthen edges, the proposed method adjusted selectivity coefficient by area step by step from a low resolution image obtained from wavelet converted images to a high resolution image and performed edge filtering in consideration of direction. Through this method, we generated a selective low pass filtering effect in areas except edges by decreasing the wavelet coefficient for pixels in spot areas, improved continuity by smoothing edges in the tangential direction, and enhanced contrast by thinning in the normal direction. Through an experiment, we compared the filtering method using a non linear anisotropic expansion model and the filtering method using wavelet contraction structure in single resolution.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.132-145
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• 2009

We present the framework for JND based Illumination and Color Restoration Using Edge-preserving filter for restoring distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computation cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small spread parameter while considering the processing time and removing the artifacts such as HALO and noise amplification. The suggested CRF (color restoration filter) can restore the natural color and correct color distortion artifact more perceptually compared with current solutions. For the automatic processing, the image statistics analysis finds suitable parameter using JND and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.289-294
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• 2004

For the purpose of image analysis, we usually take the application method relying on the various mathematical theories. On the respect of image as two variable function one may uses the gradient vector or several type of energy functions induced by the conventional (partial) derivative. We also have used the tangent plane or curvature vector from the concept of differential geometry {**]. However, these mathematical tools my assume that the given function should be sufficiently smoothing enough to depict every local variation continuously. But the real application of these mathematical methods to the natural images or phenomena may occur the ill-posed problem. In this paper, we have defined the weak derivative as a loose form of the derivative so that it my applied to the irregular case with less ill-posed problem.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.81-88
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• 2011

Mini Double Gears Frame is critical part of PDP and also produces couple hundred thousand every month. In the process of mass production, product inspection is very important process. Double Gear, one of the part of machine, was inspected by human eyes which caused mistakes and slow progress. To achieve the speed and accuracy the system was compensated by vision system which is inspecting automatically. The focus value is measured based on the fact that high contrast images have much high frequency edge information. High frequency term of the image is extracted using the high-pass filter and the sum of the high frequency term is used as the focus value. We used a Gaussian smoothing filter to reduce the noise and then measures the focus value using the modified Laplacian filter called a Sum modified Laplacian Focus values for the various lens positions are calculated and the position with the maximum focus value is decided as the focused position. The focus values calculated in various lens position showed the Gaussian distribution. We proposed a method to estimate the best focus position using the Gaussian curve fitting. Focus values of the uniform interval lens positions are calculated and the values are used to estimate the Gaussian distribution parameters to find the best focus position.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.320-328
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• 1999

The Laplacian operator is usually used as a regularization operator which may be used as any differential operator in the regularization iterative restoration. In this paper, several kinds of differential operator and 1-H operator that has been used in our lab as well, as a regularization operator, were compared with each other. In the restoration of noisy motion-blurred images, 1-H operator worked better than Laplacian operator in flat region, but in the edge the Laplacian operator operated better. For noisy gaussian-blurred image, 1-H operator worked better in the edge, while in flat region the Laplacian operator resulted better. In regularization, smoothing the noise and resorting the edges should be considered at the same time, so the regions divided into the flat, the middle, and the detailed, which were processed in separate and compared their MSE. Laplacian and 1-H operator showed to be suitable as the regularization operator, while the other differential operators appeared to be diverged as iterations proceeded.

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.77-84
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• 2007

The intima media thickness(IMT) of the carotid artery from B mode ultrasound images has recently been proposed as the most useful index of individual atherosclerosis and can be used to predict major cardiovascular events. Ultrasonic measurements of the IMT are conventionally obtained by manually tracing interfaces between tissue layers. The drawbacks of this method are the inter and intra observer variability and its inefficiency. In this paper, we present a multiresolution snake method combined with the dynamic programming, which overcomes the various noises and sensitivity to initialization of conventional snake. First, an image pyramid is constructed using the Gaussian pyramid that maintains global edge information with smoothing in the images, and then the boundaries are automatically detected in the lowest resolution level by minimizing a cost function based on dynamic programming. The cost function includes cost terms which are representing image features and geometrical continuity of the vessel interfaces. Since the detected boundaries are selected as initial contour of the snake for the next level, this automated approach solves the problem of the initialization. Moreover, the proposed snake improves the problem of converging th the local minima by defining the external energy based on multiple image features. In this paper, our method has been validated by computing the correlation between manual and automatic measurements. This automated detection method has obtained more accurate and reproducible results than conventional edge detection by considering multiple image features.