• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.20-29
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• 2018

This study investigated the effect of PR communication of local government on the relationship between the local government and the public and the image of the local government, focusing on the official blog of Busan Metropolitan City, 'Cool Busan.' It also examined the mediating role of organization-public relations. As a result, 'interactivity' and 'interest' among the characteristics of social media information have a statistically significant effect on organization-public relationship and municipal image. And balance' was found to affect the image of local government. In addition, the mediating role of the organization-public relations subfactors has been proved in the influence of the local government social media information characteristics on the local government image.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.2
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• pp.129-142
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• 2014

We propose a variational segmentation model based on statistical information of intensities in an image. The model consists of both a local region-based energy and a global region-based energy in order to handle misclassification which happens in a typical statistical variational model with an assumption that an image is a mixture of two Gaussian distributions. We find local ambiguous regions where misclassification might happen due to a small difference between two Gaussian distributions. Based on statistical information restricted to the local ambiguous regions, we design a local region-based energy in order to reduce the misclassification. We suggest an algorithm to avoid the difficulty of the Euler-Lagrange equations of the proposed variational model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1194-1200
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• 2006

In this paper, we propose an adaptive MAP (Maximum A Posteriori) high-resolution image reconstruction algorithm using local statistics. In order to preserve the edge information of an original high-resolution image, a visibility function defined by local statistics of the low-resolution image is incorporated into MAP estimation process, so that the local smoothness is adaptively controlled. The weighted non-quadratic convex functional is defined to obtain the optimal solution that is as close as possible to the original high-resolution image. An iterative algorithm is utilized for obtaining the solution, and the smoothing parameter is updated at each iteration step from the partially reconstructed high-resolution image is required. Experimental results demonstrate the capability of the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1035-1041
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• 2016

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.104-110
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• 2016

Dense local image descriptors like SIFT are fruitful for capturing salient information about image, shown to be successful in various image-related tasks when formed in bag-of-words representation (i.e., histograms). In this paper we consider to utilize these dense local descriptors in the object tracking problem. A notable aspect of our tracker is that instead of adopting a point estimate for the target model, we account for uncertainty in data noise and model incompleteness by maintaining a distribution over plausible candidate models within the Bayesian framework. The target model is also updated adaptively by the principled Bayesian posterior inference, which admits a closed form within our Dirichlet prior modeling. With empirical evaluations on some video datasets, the proposed method is shown to yield more accurate tracking than baseline histogram-based trackers with the same types of features, often being superior to the appearance-based (visual) trackers.

• Archives of design research
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• v.16 no.1
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• pp.63-72
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• 2003

The purpose of this study is to understand the character of concerned local area through using roadside space that is space for daily experience of citizen as target, extracting symbolic image reconsidering the historical and cultural character and clarifying the local identity on the basis of it. Through applying image of local symbolism and future-oriented roadside to street furniture, I tried to express local symbolism and through composing symbolic roadside of local that can be newly recognized as unique street, I tried to give a local symbolism and compose active roadside environment. Through providing basic material and actual design example, this paper tried to activate characterized local culture. As the method to approach design of symbolic roadside, the researcher divided local symbolic image into present local image and future-oriented image through selecting the roadside that historical element is lost and urbanization is achieved as target. The researcher characterized local roadside, using street furniture as symbolic tool of future-oriented roadside on the basis of symbolic image extracted from image evaluation testing. This paper has the meaning to suggest one direction for extracting symbolism when organizing distinguished roadside through applying symbolic image to roadside environmental facility, helping for of local resident's sense of place, his self-esteem and love for his hometown and public authority's establishing and promoting the policy concerned to the context of this paper.

• Science of Emotion and Sensibility
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• v.12 no.3
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• pp.331-340
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• 2009

As the cultural importance of local environment has been increasing, interests of local residents for city design has also increased. City design can inspire local residents' pride and redefine the city image to both local and outside world. Therefore, this study analyzes the city's(Pohang city) status, environmental characteristics, and local residents' design image preference; and based on the analysis, this study suggests standard design for public facilities that constitute "streets", that can realize the city image identity. For the suggestion, scenery image and public facilities status of the twenty-four areas in the city were analyzed. Also, to decide the design direction of public facilities that can constitute the city's consistent ideology, thoughts, and image, design preference factors for public facilities by local residents were surveyed and analyzed. The design guidelines and a standard design were established for total of thirty-one public facilities based on the analysis. The outcome will enable provision of communication media to express the charming city image and also of material that can be reflected in the integrated city scenery project in the future.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.595-607
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• 2010

This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.375-380
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• 2017

This paper has proposed a single image based fog degree quantification method by measuring both transmission and local contrast. The proposed method estimates the foggy expected regions from transmission, and then assesses the size of regions of which transmission values are foggy expected ones and the range of local contrast value on such regions. Compared with fog degree gauged by the scattering coefficient measurement sensor, the proposed method quantifies the fog degree with more than 95% accuracy for images containing various objects and environments. We also developed a technique that measures the local contrast values in process of measuring transmission values. So, the proposed method does not increase complexity compared to the existing transmission method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.