• Journal of Multimedia Information System
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• v.4 no.2
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• pp.89-92
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• 2017

This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.158-167
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• 2015

This study presents a new method to improve the speed of high quality volume rendering. We improve the speed of ambient occlusion which is one of the global illumination techniques used in traditional volume visualization. Calculating ambient occlusion takes much time because it determines an illumination value of a sample by integrating opacities of nearby samples. This study proposes an improved method for this by using local statistics such as averages and standard deviations. We calculate local statistics for each volume block, a set of nearby samples, in pre-processing time. In the rendering process, we efficiently determine the illumination value by assuming the density distribution as a normal distribution. As the results, we can generate high quality images that combine ambient occlusion illumination with local illumination in real time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.37-45
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• 2007

We propose an adaptive image enhancement method for epigraphic images, which is based on local statistics. Local statistics of the image are utilized for adaptive realization of the enhancement, that controls the contribution of the smoothing or sharpening paths. Image contrast enhancement occurs in details and noises are suppressed in smooth areas. For modeling the epigraphic image, pre~process is achieved by HSDI(Hanzi squeezed digital image). We have calculated the local statistics from this HSDI model. Application of this approach to HSDI has shown that processing not only smooths the background areas but also improves the subtle variations of edges, so that the word regions can be enhanced. Experimental results show that the proposed algorithm has better performance than the conventional image enhancement ones.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.337-344
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• 1998

We analyze statistical reliability about local area results of '96 Survey of Family Consumption Behavior by the National Statistical Office. Also, we suggest reliable estimation procedures for reducing statistical errors in local ares estimation problem.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.3-6
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• 2003

A nonlinear iterative filtering based on local statistics and anisotropic diffusion is introduced. Local statistics determines the diffusion coefficient at each iteration step. Anisotropic diffusion can be seen as estimates a piecewise smooth image from the noisy input image in the experimental section, our results are shown to suppress noise with preserving the edges. Therefore, it enhances the image and improves performance.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.63-71
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• 1995

We have consider the study of local influence for smoothing parameter estimates in spline regression model with heteroscedasticity. Practically, generalized cross-validation does not work well in the presence of heteroscedasticity. Thus we have proposed the local influence measure for generalized cross-validation estimates when errors are heteroscedastic. And we have examined effects of diagnostic by above measures through Hyperinflation data.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.849-858
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• 2012

Today, local environmental factors has an influence on our society. Local environmental factors, as well as weather-related natural phenomena, social phenomena are also included. In this paper, numeric factors and categorical factors were analyzed, looking for a local environmental factors affecting the company's sales.Sales model by performing a regression analysis based on this was implemented.Sales model considering the local environment had an accuracy of 88.89%.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.77-87
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• 2001

Some asymptotic results on the local likelihood density estimator of Copas(1995) are derived when the locally parametric model has several parameters. It turns out that it has the same asymptotic mean squared error as that of Hjort and Jones(1996).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.17-23
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• 2010

In this paper, we present an adaptive noise removal method using local statistics and generalized Gaussian filter. we propose a generalized Gaussian filter for removing noise effectively and detecting noise adaptively using local statistics based human visual system. The simulation results show the objective and subjective capabilities of the proposed algorithm.

• Journal of the Korean Statistical Society
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• v.30 no.3
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• pp.467-480
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• 2001

This paper considers the use of local $\phi$-divergence measures between posterior distributions under classes of perturbations in order to investigate the inherent robustness of certain classes. The smaller value of the limiting local $\phi$-divergence implies more robustness for the prior or the likelihood. We consider the cases when the likelihood comes form the class of weighted distribution. Two kinds of perturbations are considered for the local sensitivity analysis. In addition, some numerical examples are considered which provide measures of robustness.