• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.2
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• pp.1-11
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• 2021

Salt and pepper is a type of impulse noise. It may appear due to an error in the image transmission process and image storage memory. This noise changes the pixel value at any position in the image to 0 (in case of pepper noise) or 255 (in case of salt noise). In this paper, we present an algorithm for SAP noise reduction. The proposed method consists of three steps. In the first step, the location of the SAP noise is detected, and in the second step, the pixel value of the detected location is restored using a weighted average of the surrounding pixel values. In the last step, a reliability matrix around the reconstructed pixels is constructed, and additional correction is performed with a weighted average using this. As a result of the experiment, the proposed method appears to have similar or higher objective and subjective image quality than previous methods for almost all SAP noise ratios.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.922-924
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• 2015

Recently, the image processing technologies using the public media such as the film, TV, camera and advertisement have been rapidly developed. However, the deterioration occurs with the image in the process of data processing, transmission and storage, and the typical cause of such deterioration is the salt and pepper noise. Typical filters to remove the salt and pepper noise include CWMF(center weighted median filter) and AMF(adaptive median filter) but such filters bring more or less insufficient characteristics of noise removal and visual error as the noise density gets higher. Thus, this paper proposed the median filter which applied the local mask segmented to 4 areas in order to remove the salt and pepper noise effectively and used PSNR(peak signal to noise ratio) as a criterion of judgment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.940-947
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• 2010

Motion Compensated Frame Interpolation(MCFI) has been used to reduce motion jerkiness for dynamic scenes and motion blurriness for LCD-panel display as post processing for high quality display. However, MCFI that directly uses the motion information often suffers from annoying artifacts such as blockiness, ghost effects, and deformed structures. So in this paper, we propose a novel edge-based adaptively weighted vector median filter as post-processing. At first, the proposed method generates an edge direction map through a sobel mask and a weighted maximum frequent filter. And then, outlier MVs are removed by average of angle difference and replaced by a median MV of $3{\times}3$ window. Finally, weighted vector median filter adjusts the weighting values based on edge direction derived from spatial coherence between the edge direction continuity and motion vector. The results show that the performance of PSNR and SSIM are higher up to 0.5 ~ 1 dB and 0.4 ~ 0.8 %, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.89-96
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• 2009

In this paper, we propose an efficient deinterlacing algorithm which is an edge dependent interpolation based on edge direction refinement. The conventional edge dependent interpolation algorithms have a visually better performance than any other Intra-field deinterlacing algorithms. However they are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method detects edge direction of around interpolated pixel and refines the edge direction using weighted median filter. Simulation results have shown the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.1-12
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• 2019

This paper proposes a new motion vector smoothing and motion compensation method to increase the frame rate of videos. The proposed method reduces false motion vector smoothing by improving the weight with reflecting accuracy to overcome the limitation of the conventional motion vector smoothing using the adaptively weighted vector median. Also, to improve the interpolated image quality of the conventional OBMC(Overlapped Block Motion Compensation), a scheme that divides an original block into 4 sub-blocks and then generates the interpolated frame using the reestimated motion vector for each sub-block is proposed. The simulation results prove that the proposed method can provide much better objective and subjective image quality than the conventional method.

• Journal of the Korean Statistical Society
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• v.10
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• pp.105-121
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• 1981

The problem of selection of a subset containing the largest of several slope parameters of regression equations is considered. The proposed selection procedure is based on the weighted median estimators for regression parameters and the median of rescaled absolute residuals for scale parameters. Those estimators are compared with the classical least squares estimators by a simulation study. A Monte Carlo comparison is also made between the new procedure based on the weighted median estiamtors and the procedure based on the least squares estimators. The results show that the proposed procedure is quite robust with respect to the heaviness of distribution tails.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.402-406
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• 1991

In this paper, we find a set of conditions on weights under which a recursive weighted median filter preserves monotone or localy monotone sequence and under which any input sequence converges to a locally monotone sequence after a finite number of passes.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.271-284
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• 2002

In this paper we consider the robust inference for the parameter of linear regression model based on weighted least squares. First we consider the sequential test of multiple outliers. Next we suggest the way to assign a weight to each observation $(x_i,\;y_i)$ and recommend the robust inference for linear model. Finally, to check the performance of confidence interval for the slope using proposed method, we conducted a Monte Carlo simulation and presented some numerical results and examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.379-381
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• 2011

The image signal is often affected by the existence of noise, noise can occur during image capture, transmission or processing phases. noises caused the degradation phenomenon and demage the original signal information. Many studies are being accomplished to restore those signals which corrupted by mixed noise. In this paper, we proposed mixed weighted filter for removing Gaussian and impulse noise. we first charge the noise type, then, Gaussian is removed by a weighted mean filter and impulse noise is removed by self-adaptive weighted median filter that can not only remove mixed noise but also preserve the details. And through the simulation, we compared with the conventional algorithms and indicated that proposed method significant improvement over many other existing algorithms and can preserve image details efficiently.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.1-4
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• 2012

Given separated points divided by a line, called a wall, in a plane, we aim to make a gate in the wall to connect the separated points to each other. In this setting, the problem is to find a location for the gate that minimizes the average distance between the points. The problem is a variant of the well-known facility location problem, which is extensively studied in the fields of operations research, location theory, theoretical computer science, and so on. In this paper, we consider the $L^1$-distance of the points in the plane. The points are projected onto the wall and so the problem is transformed to a proximity problem of points on a line. Then it is shown that the transformed problem is related to the weighted median problem of points on the line. Therefore, we obtain an O(n log n)-time algorithm to solve our problem.