• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.598-604
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• 2012

Image signal is corrupted by various noises in image processing, many studies are being accomplished to restore those images. In this paper, we proposed a cascade filter algorithm for removing random valued impulse noise. The algorithm consists two steps that noise detection and noise elimination. Variance of filtering mask and center pixel variance are calculated for noise detection, and the noise pixel is replaced by estimated value which first apply switching self adaptive weighted median filter and finally processed by modified weight filter. Considering the proposed algorithm only remove noise and preserve the uncorrupted information that the algorithm can not only remove noise well but also preserve edge.

• Journal of the Korea Computer Graphics Society
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• v.18 no.4
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• pp.1-8
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• 2012

We present improved deformation energy to enhance the visual quality of a shape deformation technique, where we preserve the local structure of an input planar shape. The deformation energy, in general, consists of several constraints such as Laplacian coordinate constraint to preserve the quality of deformed silhouette edges, mean value coordinates and edge length constraints to preserve the quality of deformed internal shape, and user-specified position constraints to control the shape deformation. When the positions of user-specified vertices change, shape deformation techniques compute the positions of the other vertices by means of nonlinear least squares optimization to minimize the deformation energy. When a user-specified vertex changes its position rapidly, it is frequently observed that the visual quality of the deformed shape decrease rapidly, which is mainly caused by unnecessary enlargement of the Laplacian vectors and unnecessary change of the edge directions along the boundary of the shape. In this paper, we propose improved deformation energy by prohibiting the Laplacian and edge length constraints from changing unnecessarily. The proposed deformation energy incorporated with well-known optimization technique can enhance the visual quality of shape deformation along the silhouette and within the interior of the planar shape while sacrificing only a little execution time.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.476-483
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• 2002

In the past 20 years or so, numerous methods to reduce speckle in SAR images have been proposed. The primary goal of these methods is to reduce speckle without destroying resolution and smearing edge information. But the experiments indicate that there is always a kind of tradeoff between smoothing out speckle and preserving edge information. In this paper, an optimal SAR speckle filter is developed. It can effectively smooth out speckle while preserve edge information.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.568-574
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• 2002

The main issue of noise reduction of image is how to preserve edge and reduce noise. Usually, The Wiener falter is used for this purpose. But the conventional Wiener filter cannot remove noise well in both edge and smooth region due to the single size estimation window. In addition, it ignores the correlation between pixels. In this paper, we propose a new noise reduction algorithm, in which adaptive estimation window is used according to property of smooth region and edge region. In order to make edge more clear, directional Gaussian mask and directional estimation window combines to the Wiener filter according to direction of edge. From the simulation results, it can be seen that the proposed algorithm showed improves performance in both PSNR arid subjective evaluation

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.333-335
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• 2011

In the transmitting process of image processing system, images always be corrupted by impulse noise, especially random-valued impulse noise. So removing the random-valued impulse noise is very important, but it is also one of the most difficult case in image processing. The most famous method is the standard median filter, but at edge, the filter has a special feature which has a tendency to decrease the preserve. As a result, we proposed a filter that detection random-valued impulse noise firstly, next to use efficient method to remove the noise and preserve the details. And through the simulation, we compared with the algorithms and indicated that proposed method significant improvement over many other existing algorithms.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.510-512
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• 1993

The weighted median hybrid filters are proposed. These filters take weighting factors in calculating the output of subfilters of median hybrid filters. The properties of weighted median hybrid filters are analysed and compared to the conventional median filter. The results indicate that these filters preserve details of edge better than and are computationally much more efficient than conventional median filter.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.44-52
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• 1996

This paper proposes a KLT-CVQ scheme using PCNN to improbe the quality of the reconstructed images at a given bit rate. By using the PCNN and classified vector quantization, we exploit the high energy compaction and compelte decorrelation capbilities of the KLT, and the pdf (probability density function) shape and space-filling advantages of the vQ to improve the performance of the proposed hybrid coding technique. In order to preserve the preceptual fetures such as the edge components in the reconstructed images, we classified the input image blocks according to the texture energy measures of the local statistics and vector-coded them adaptively, and thereby reduces the possible edge degradation in the reconstructed images. The results of the computer simulations show that the performance of the proposed KLT-CVQ is higher than that of the KLT-CSQ or the DCT-CVQ in the quality of the reconstructed images at a given bit rate.

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.133-140
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• 2020

This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.3
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• pp.470-476
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• 1997

The dynamic characteristics of industrial processes frequently cause an abnormal situation which is undesirable in terms of the productivity and the safety of workers. The goal of fault-tolerance is to continue performing certain activities even after the failure of some system cononents. A fault-tolerant intelligent monitoring and control system which is robust under disturbances is proposed in this paper. Specifically, the fault-tolerant monitoring scheme proposed consists of two process models and the inference module to preserve such a robustness. The results of turning experiments demonstrate the effectiveness of the fault-tolerant scheme in the presence of built-up edge.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.29-32
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• 1990

The method for enhancing the edges from medical images is described. The various methods are tested for the medical Images contaminated by noises, such as weighted averaging based on local probabilities, unsharp masking techniques, and proposed combined techniques. As a result, the combined technique using the median filtering and edge masks in six directions is well suited to remove the noises as to as to preserve the edges. Experimental results and computational procedures are presented.