• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.637-646
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• 2009

This study aims at granting maximum high values to local brand images as megatrend in global markets by monitoring local differentiations which local images in each area are classified in abstraction on the side of cognitive aspects of consumers and finally achieving the redefinition of domestic markets with differentiation strategies for revitalizing cultural communication tools in terms of the creation of future local marketing strategies. This study newly classifies the cognitive aspects of domestic consumers into 4 distinguished patterns for creating an image of each local area and analyzes image creation factors for each local image in 5 aspects affecting the image creation of local brands.

• 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.

• KIEAE Journal
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• v.10 no.1
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• pp.73-83
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• 2010

In urban regeneration, resident participation and respect of residents' need have become a major important issue. The purpose of this study is to identify residential area improvement characteristics expected by local residents. Data used for this study were collected from survey which used questionnaire and village image map construction tool kit, developed for facilitating the residents' participation in an actual housing improvement area at Kwngjoo, Korea. The major contents surveyed through questionnaire were first, future images of the area second, directions of improvement third, preferred architectural types such as high or low rise buildings. and a total of 335 data was collected within 4 days during 12-14 December, 2008. The kit was used by parents of students at a local elementary school, and 205 image maps were collected. Content analysis was to analyse characteristics of villages shown in the constructed image maps. Lynch's five elements were utilized to select areas for analysis. As a result, types of buildings desired by residents at the selected four local areas were identified. In general, residents desired their village to be improved with low and mid rise buildings, respecting existing cultural assets. This study showed that there is certain characteristics in relation to the selected areas. Besides, the tool kit used this study showed the effectiveness in collecting opinions from young households in the improvement area within a short time. The tool is expected to be useful in attracting residents and in facilitating participation of wide range of local residents by improving the constraints stemming from time and space.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.933-935
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• 2015

Currently, image processing is being utilized in various fields and many studies on the image restoration is being progressed in order to eliminate the noise being generated during the process of transmitting, processing and storing of image. There are various types of noises included in the image according to the causes and types but AWGN is the most representative. In this paper, an algorithm was proposed which applies the variables differently according to the differences in surrounding pixels and central pixels within the local mask in order to mitigate the AWGN included in the image.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.293-296
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• 1996

In this paper, we studied two image characteristics, similarity and smoothness, which give rise to local and global redundancy in image representation. The similarty means that any patterns in the image repeat itself anywhere in the rest of image. The smoothness means that the gray level values within a given block vary gradually rather than abruptly. In this sense, we propose a lossless medical image compression scheme which exploits both types of redundancy. This method segments the image into variable size blocks and encodes them depending on characteristics of the block. The proposed compression schemes works better than other compression schemes such as the huffman, the arithmetic, the Lempel-Ziv and the lossless scheme of JPEG.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.827-835
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• 2019

In the pooling stage of a full reference image quality assessment (FR-IQA) technique, the global perceived quality for any distorted image is usually measured from the quality of its local image patches. But all the image patches do not have equal contribution when estimating the overall visual quality since the degree of degradation on those patches depends on various considerations i.e., types of the patches, types of the distortions, distortion sensitivities of the patches, saliency score of the patches, etc. As a result, weighted pooling strategy comes into account and different weighting mechanisms are used by the existing FR-IQA methods. This paper performs a thorough analysis and proposes a novel weighting function by considering the luminance adaptation as well as the visual saliency effect to offer more appropriate local weights, which can be adopted in the existing FR-IQA frameworks to improve their prediction accuracy. The extended experimental results show the effectiveness of the proposed weighting function.

• Journal of the Korean association of regional geographers
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• v.11 no.5
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• pp.405-425
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• 2005

Transition from mass tourism to post tourism is closely related with developing various types of cultural tourism. This study attempts to construct a conceptual framework of the development of cultural tourism through identifying the existing development stages of cultural tourism sites from birth to full development. This study clarifies that there exists an organic system among tourism, cultural activities and the production of cultural artifacts. It also found that development of cultural tourism sites goes through the following three stages: positioning and building place image, hard branding, and constructing local system. This study analyzes several key elements for respective of stages, which proved helpful in understanding the development mechanism of cultural tourism sites. It also tries to analyze tourism from an integrated, geographical perspective. The analysis gives us an understanding to the relations between tourism and various aspects of regional society and economy, thus contributing to the development of a system that will lead to active interchanges among those factors. Most of the theoretical background of this study: place identity, place image, activity space, local system and network are based on the concepts and ideas of human geography.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2541-2551
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• 1996

Human visual systems are sensitive to noise on the flat intensity area. But it becomes less sensitive on the edge area. Recently, many types of spatially adaptive image restoration methods have been proposed, which employ the above mentioned huan visual characteristics. The present paper presents an adaptive image restoration method, which increases sharpness of the edge region, and smooths noise on the flat intensity area. For edge detection, the proposed method uses the visibility function based on the local variance on each pixel. And it adaptively changes the regularization parameter. More specifically, the image to be restored is divided into a number of steps from the flat area to the edge regio, and then restored by using the finite impulse response constrained least squares filter.