• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.9
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• pp.559-566
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• 2005

An effective do-blurring algorithm is proposed to remove the blur of the even and the odd line images of the interlaced scan type camera. n the object or the camera moves fast while the interlaced scan type digital camera is acquiring images, blur is often created due to the misalignment between two images of even and odd lines. In this paper, the blurred original image is separated into the even and the odd line images of the half size. Two full sized images are generated using interpolation technique based on these two in ages. Again, these images are signed and combined through the processes of feature extraction, matching, sub-pixel matching, outlier removal, and mosaicking. De-blurring simulations about the images of different camera motions have been done.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.41-52
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• 2018

This paper presents a method for accurate camera self-calibration based on SIFT Feature Detection and image quality assessment. We performed image quality assessment to select high quality images for the camera self-calibration process. We defined high quality images as those that contain little or no blur, and have maximum contrast among images captured within a short period. The image quality assessment includes blur detection and contrast assessment. Blur detection is based on the statistical analysis of energy and standard deviation of high frequency components of the images using Discrete Cosine Transform. Contrast assessment is based on contrast measurement and selection of the high contrast images among some images captured in a short period. Experimental results show little or no distortion in the perspective view of the images. Thus, the suggested method achieves camera self-calibration accuracy of approximately 93%.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.818-833
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• 2017

This paper introduces a new algorithm that renders motion blur using triangular motion paths. A triangle occupies a set of pixels when moving from a position in the start of a frame to another position in the end of a frame. This is a motion path of a moving triangle. For a given pixel, we use a motion path of each moving triangle to find a range of time that this moving triangle is visible to the camera. Then, we sort visible time ranges in the depth-time dimensions and use bitwise operations to solve the occlusion problem. Thereafter, we compute an average color of each moving triangle based on its visible time range. Finally, we accumulate an average color of each moving triangle in the front-to-back order to produce the final pixel color. Thus, our algorithm performs shading after the visibility test and renders motion blur in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.349-355
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• 2015

Underwater robots generally show better performances for tasks than humans under certain underwater constraints such as. high pressure, limited light, etc. To properly diagnose in an underwater environment using remotely operated underwater vehicles, it is important to keep autonomously its own position and orientation in order to avoid additional control efforts. In this paper, we propose an efficient method to assist in the operation for the various disturbances of a remotely operated vehicle for the diagnosis of underwater structures. The conventional AHRS-based bearing estimation system did not work well due to incorrect measurements caused by the hard-iron effect when the robot is approaching a ferromagnetic structure. To overcome this drawback, we propose a sensor fusion algorithm with the camera and AHRS for estimating the pose of the ROV. However, the image information in the underwater environment is often unreliable and blurred by turbidity or suspended solids. Thus, we suggest an efficient method for fusing the vision sensor and the AHRS with a criterion which is the amount of blur in the image. To evaluate the amount of blur, we adopt two methods: one is the quantification of high frequency components using the power spectrum density analysis of 2D discrete Fourier transformed image, and the other is identifying the blur parameter based on cepstrum analysis. We evaluate the performance of the robustness of the visual odometry and blur estimation methods according to the change of light and distance. We verify that the blur estimation method based on cepstrum analysis shows a better performance through the experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10B
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• pp.1953-1962
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• 1999

While acquiring the image, the shaking of the image capturing equipment or the object seriously damages the image quality. This phenomenon, which degrades the clarity and the resolution of the image is called motion blur. In this paper, a newly defined function is introduced for finding the degree and the length of the motion blur. The domain of this function defined as Peak-trace domain. In The Peak-trace domain, the noise dominant region for calculating the noise variance and the signal dominant region for extracting the degree and the length of the motion blur are defined and analyzed. Using the information of the Peak-trace in the signal dominant region, we can find the direction of the motion regardless of the noise corruption. Weighted least mean square method helps extracting the Peak-trace more precisely. After getting the direction of the motion blur, we can find the length of the motion blur based on one dimensional Cepstrum. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.

• Journal of Fashion Business
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• v.24 no.4
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• pp.144-160
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• 2020

Today, the development of innovative technologies is accompanied by changes in the industrial structure and the Big Blur phenomenon, where the boundaries in various fields are blurred. The purpose of this study was to view the Big Blur phenomenon as a big paradigm shift in the 21st century and derive environmental changes and characteristics of the Korean fashion market. The research method included an analysis of the fashion brands after 2015. Through this study, we intended to establish a framework for understanding the changes in the fashion market from the perspective of Big Blur and discuss the direction of brand marketing. The research results showed the hyperlinks, connectivity, openness, homeostasis, synchronicity, mobility, interactivity, and brand experience of online and offline spaces beyond the boundaries of virtual space and offline physical spaces such as online physical and spatial viewpoints. It also showed the characteristics. The characteristics from the socio-cultural point of view were characteristic of diversity, mixture, coexistence, composability, and pluralism beyond the traditional socio-cultural and regulatory scopes. Hip hop fashion, street fashion, unisex, genderless, androgynous fashion, and kid fashion are the backbone of the Big Blur and are becoming important factors in fashion. The characteristics of the market and economic viewpoint are prosumers that play roles both as producers and consumers. It shows the extensibility of consumers as producers, the cohesiveness of producers and consumers, the cooperation, and the interconnectivity.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.200-209
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• 2016

This paper proposes a non-uniform de-blur algorithm using IMU sensor and a long/short exposure-time image pair to efficiently remove the blur phenomenon. Conventional blur kernel estimation algorithms using sensor information do not provide acceptable performance due to limitation of sensor performance. In order to overcome such a limitation, we present a kernel refinement step based on images having different exposure times which improves accuracy of the estimated kernel. Also, in order to figure out the phenomenon that conventional non-uniform de-blur algorithms suffer from severe degradation of visual quality in case of large blur kernels, this paper a homography-based residual de-convolution which can minimize quality degradation such as ringing artifacts during de-convolution. Experimental results show that the proposed algorithm is superior to the state-of-the-art methods in terms of subjective as well as objective visual quality.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.362-371
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• 2014

Blur variation caused by camera de-focusing provides a proper cue for depth estimation. Depth from Defocus (DFD) technique calculates the blur amount present in an image considering that blur amount is directly related to scene depth. Conventional DFD methods use two defocused images that might yield the low quality of an estimated depth map as well as a reconstructed infocused image. To solve this, a new DFD methodology based on infocused and defocused images is proposed in this paper. In the proposed method, the outcome of Subbaro's DFD is combined with a novel edge blur estimation method so that improved blur estimation can be achieved. In addition, a saliency map mitigates the ill-posed problem of blur estimation in the region with low intensity variation. For validating the feasibility of the proposed method, twenty image sets of infocused and defocused images with 2K FHD resolution were acquired from a camera with a focus control in the experiments. 3D stereoscopic image generated by an estimated depth map and an input infocused image could deliver the satisfactory 3D perception in terms of spatial depth perception of scene objects.

• Journal of Korean Ophthalmic Optics Society
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• v.20 no.3
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• pp.355-362
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• 2015

Purpose: To investigate the effects of the transmittance of diffusive blurson visual acuity and contrast sensitivity. Methods: Visual acuity and contrast sensitivity were measured by using Optec$^{(R)}$ 6500 in Healthy 30 subjects aged $22.83{\pm}0.50$ (male 13, female 17) who were recruited from university students. Cataract simulator was used as a tool for diffusive blur. Visual acuity and contrast sensitivity were measured with varying the transmittance of diffusive blur in order to simulate progression of cataract and concentration in fog. Results: Visual acuity was reduced proportionally with decreasing the transmittance of the diffusive blur as follows: $VA(T)=1.84{\times}10^{-2}T-0.645$. Contrast sensitivity was decreased in all spatial frequencies. Contrast sensitivity in a high spatial frequency band was a greater effect and was off the normal range of contrast sensitivity. The peak of contrast sensitivity was moved in the direction to low frequency. From an intersection point of contrast sensitivity function, we could calculated the transmittance of the diffusive blur being off the normal range and the shift to peak spatial frequency. The peak of contrast sensitivity function was observed to move from 6 to 3 cpd at transmittance of about 78.70%, the contrast sensitivities for all frequencies at transmittance of about 69.71% were deviated from the normal range. Conclusions: The transmittance of diffusive blur causes a reduction in visual acuity and contrast sensitivity, a deviation of normal range of contrast sensitivity, and a shift of peak contrast sensitivity. Therefore the more attention is required when suffering from cataracts or driving in fog.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.2
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• pp.145-149
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• 2005

In a artificial hypermetropia with the accommodative response, we investigated a diameter of blur circle as a function of test lens refractive power. In a schematic eye model of the hypermetropia, the second focal length along to accommodated power of the crystal lens are calculated as a function of test lens power and, also distance between the retina and exit pupil are calculated as a function of accommodated power. As these results are compared, the size of blur circle on the retina are obtained.