• International journal of advanced smart convergence
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• v.12 no.2
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• pp.127-134
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• 2023

Existing studies on this topic have focused on the effect of online content quality on consumer attitudes and behavior, with very few illustrating the effect of influencer image on consumer attitudes and behavior. The purpose of this study intents to reveal how influencer image affect consumer behavior. We have developed an image transfer theory-based research model to reveal how influencers transfer their image to endorsed products to influence consumer behavior. The results show that influencer image positively affects satisfaction, which in turn affects the product's cognitive and affective images in the vlog. Moreover, it was found that a product's cognitive image and affective image influence consumer behavior intention. Furthermore, purchase experience exhibits significant differences in its path. Based on these results, the social media-related research theoretical implication will be offered, and managerial implications will be provided for foreign brand promotion strategies

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3672-3684
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• 2015

Recently, the standardization of backward compatible JPEG image coding for high dynamic range (HDR) image has been undertaken to establish an international standard called "JPEG XT." The JPEG XT consists of two layers: the base layer and the residual layer. The base layer contains tone mapped low dynamic range (LDR) image data and the residual layer contains the error signal used to reconstruct the HDR image. This paper gives the result of a study to evaluate the overall performance of tone mapping operators (TMOs) for this standard. The evaluation is performed using five HDR image datasets and six TMOs for profiles A, B, and C of the proposed JPEG XT standard. The Tone Mapped image Quality Index (TMQI) and no reference image quality assessment (NR IQA) are used for measuring the LDR image quality. The peak signal to noise ratio (PSNR) is used to evaluate the overall compression performance of JPEG XT profiles A, B, and C. In TMQI and NR IQA measurements, TMOs using display adaptive tone mapping and adaptive logarithmic mapping each gave good results. A TMO using adaptive logarithmic mapping gave good PSNRs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.366-385
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• 2013

In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.91-96
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• 2014

Mobile image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes a new efficient and effective mobile image retrieval method that applies a weighted combination of color and texture utilizing spatial-color and second order statistics. The system for mobile image searches runs in real-time on an iPhone and can easily be used to find a specific image. To evaluate the performance of the new method, we assessed the iPhone simulations performance in terms of average precision and recall using several image databases and compare the results with those obtained using existing methods. Experimental trials revealed that the proposed descriptor exhibited a significant improvement of over 13% in retrieval effectiveness, compared to the best of the other descriptors.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.590-599
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• 2018

Multivariate finite mixture model is becoming more and more popular in image processing. Performing image denoising from image patches to the whole image has been widely studied and applied. However, there remains a problem that the structure information is always ignored when transforming the patch into the vector form. In this paper, we study the operator which extracts patches from image and then transforms them to the vector form. Then, we find that some pixels which should be continuous in the image patches are discontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose a new operator which may keep more information when extracting image patches. We compare the new operator with the old one by performing image denoising in Expected Patch Log Likelihood (EPLL) method, and we obtain better results in both visual effect and the value of PSNR.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.325-333
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• 2010

Image registration involves overlapping images of an identical region and assigning the data into one coordinate system. Image registration has proved important in remote sensing, enabling registered satellite imagery to be used in various applications such as image fusion, change detection and the generation of digital maps. The image descriptor, which extracts matching points from each image, is necessary for automatic registration of remotely sensed data. Using contrast enhancement algorithms such as histogram equalization and image stretching, the normalized data are applied to the image descriptor. Drawing on the different spectral characteristics of high resolution satellite imagery based on sensor type and acquisition date, the applied normalization method can be used to change the results of matching interest point descriptors. In this paper, the matching points by scale invariant feature transformation (SIFT) are extracted using various contrast enhancement algorithms and injection of Gaussian noise. The results of the extracted matching points are compared with the number of correct matching points and matching rates for each point.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.70.4-70.4
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• 2019

Image super-resolution (SR) is a technique that enhances the resolution of a low resolution image. In this study, we use three SR models (RCAN, ProSRGAN and Bicubic) for enhancing solar SDO/HMI magnetograms using deep learning. Each model generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). The pixel resolution of HMI is about 0.504 arcsec. Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained three models with HMI images in 2014 and test them with HMI images in 2015. We find that the RCAN model achieves higher quality results than the other two methods in view of both visual aspects and metrics: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is also much better than the conventional bi-cubic interpolation. We apply this model to a full-resolution SDO/HMI image and compare the generated image with the corresponding Hinode NFI magnetogram. As a result, we get a very high correlation (0.92) between the generated SR magnetogram and the Hinode one.

• Journal of the Korean Institute of Landscape Architecture
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• v.35 no.1 s.120
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• pp.59-68
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• 2007

This article statistically analyzed contributive levels of district image based on an effect and a similarity index through the evaluation of citizens and suggested the efficient management system of a city image according to the results. For this study, Busan City was selected as a case city by the preceding literature and was investigated concerning district image and city image through a questionnaire. The new evaluation method for analysis of a city image was presented in this process. The results of this research are as follows: 1. Busan City has a substantial positive and culturally unique image, and each of its districts have other image characteristics. for example, the CBD district has a positive image, and the sea shore district has a busy and prosperous image, but the backward sea shore district has an image of stagnancy. 2. The image of Yeonje-gu has the largest effect on the image of Busan. Next in influence are Jung-gu, Saha-gu, Suyoung-gu, respectively. The effect index is closely connected with the variance of evaluative adjectives. 3. Busanjin-gu and Haeundae-gu have similar images to Busan City. Next in similarity are Nam-gu, Jung-gu, Youngdo-gu, Suyoung-gu, respectively. The similarity index is closely connected with the correlation of evaluative adjectives. Busan City and its districts can establish their image strategies with the above analyzed results. This study is meaningful in that a statistical evaluative method was proposed. With continued follow-up research, this study may serve as a systematic and logical model to improve the urban landscape and image.

• Korean Journal of Human Ecology
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• v.20 no.5
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• pp.1025-1034
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• 2011

The purpose of this study was to examine the evaluation of fabric characteristics on the drapability, texture image and preference of blouse fabrics, and to analyze the effects of the texture image, objective and subjective drapability on the preference. As specimen, silk and polyester fabrics were collected. 52 female subjects evaluated 16 specimens with semantic differential scale of 18 fabric image and 20 sensibility. Data were analyzed through factor analysis, pearson correlational coefficient using spss win 12.0. For the evaluation, structural characteristics such as fiber contents, weave type, weight and thickness were analyzed. The results were as follows: The evaluation results of objective and subjective drapability showed differences. Sensory image factors of blouse fabrics were 'surface smoothness', 'elasticity', 'weight' and 'flexibility'. Sensibility image factors were 'elegance', 'classic', 'characteristic' and 'mannish'. 'Elegance', 'classic' and 'characteristic' of sensibility images showed high correlation with 'surface smoothness' and 'elasticity' of sensory image, also 'mannish' of sensibility image showed significant correlation with 'weight' of sensory image. The significant fabric characteristics affecting objective drapability were density, weight, thickness. The significant texture image factors affecting objective drapability were 'weight', 'flexibility' of sensory image and 'elegance' of sensibility image. On the other hand, the significant factors affecting subjective drapability were thickness of fabric characteristics and 'elegance', 'characteristic', 'mannish' of sensibility images. 'Elegance', 'characteristic' and 'classic' of sensibility image, 'elasticity' of sensory image and subjective drapability affected on the purchase preference.

• Journal of the Korean Society of Costume
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• v.62 no.4
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• pp.58-68
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• 2012

Personal image concerns a person's talent, expertise, as well as the internal and external image. It is a core value that differentiates one individual from another. As personal branding via personal image management has become more important, there is a fast-growing number of online systems that provide self-test programs to analyze one's style and habits and also provide expert advice for not only styles but lifestyles as well. This study develops a systematic and objective personal image consulting system and offers basic information for the research of personal image making. For that purpose, the study attempts to examine the present state of global companies that use online image consulting programs and analyze their digital content. The results are as follows: 1) two domestic companies, Colorz and Atzine, and seven foreign companies, notably Covet and Boutique, were brisk in business; 2) two types of personal image-diagnosis programs - Visual search and Virtual matching - are now in operation; and 3) mobile applications exist as an evolved personal image-diagnosis program. With an increased interest in such programs, various companies at home and abroad are establishing systematic and scientific analysis systems, which are needed for personal image-making online. Under these circumstances, domestic companies are also urged to enhance levels of image-diagnosis content and actual commercialization and utilization, to develop programs that enable objectified, systematic personal image-making. To this end, the results of this study may serve as a helpful tool to consider future directions.