• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.375-382
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• 2010

In this study, we propose a robust estimator of the multivariate location parameter by means of the spatial median based on data trimming which extending trimmed mean in the univariate setup. The trimming quantity of this estimator is determined by the bootstrap method, and its covariance matrix is estimated by using the double bootstrap method. This extends the work of Jhun et al. (1993) to the multivariate case. Monte Carlo study shows that the proposed trimmed spatial median estimator yields better efficiency than a spatial median, while its covariance matrix based on double bootstrap overcomes the under-estimating problem occurred on single bootstrap method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.237-243
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• 2015

In recent image processing, active researches have been made along with rapid development in digital times. However, it is know that the image degradation occurs due to various external factors in the processes of image data processing, transmission and storage, and the main reason of image degradation is due to the noise. Typical methods to remove the noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter) and these methods have a little bit lacking noise reduction characteristics in mixed noise environments. Therefore, in order to remove the mixed noise, image restoration filter processing algorithm was suggested in this paper which processes by applying the median value of the mask and space weighted value after noise judgment. And for the objective judgment, it was compared with existing methods and PSNR(peak signal to noise ratio) was used as a judgment standard.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.227-229
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• 2021

The modern society is advancing from the analog era to the digital imaging era, and in line with the trend of this era, various imaging devices such as exploration robots, medical equipment, and CCTV are helping our daily life a lot. However, noises caused by various causes in digital images not only cause image deterioration, but also deteriorate and deteriorate image quality. A typical noise is AWGN, and types of filters to remove it include an average filter, a median filter, and an alpha-trimmed average filter, but these filters have a disadvantage in that they show somewhat inadequate noise reduction performance in the high frequency region. Therefore, in this paper, a modified spatial division average filter based on standard deviation is proposed to effectively reduce AWGN existing in the high frequency region of the image.