• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.67-71
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• 2016

This paper addresses a problem of defocus map recovery from single image. We describe a simple effective approach to estimate the spatial value of defocus blur at the edge location of the image. At first, we perform a re-blurring process using Gaussian function with input image, and calculate a gradient magnitude ratio with blurring amount between input image and re-blurred image. Then we get a full defocus map by propagating the blur amount at the edge location. Experimental result reveals that our method outperforms a reliable estimation of depth map, and shows that our algorithm is robust to noise, inaccurate edge location and interferences of neighboring edges within input image.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.562-569
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• 2010

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the blurring of magnified image. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the blurring of magnified image. As a result, the nearest neighbor interpolation, which is the most frequently applied algorithm for the existing image interpolation algorithm, shows that the identification of a magnified image is not possible. Therefore, this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson' curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter, this study will develop an interpolation algorithm that has an excellent improvement for the boundary of the image and continuous and flexible property by using the NURBS, Ferguson' complex surface, and Bezier surface used in CAD/CAM engineering based on the results of this study.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.9-17
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• 2010

This paper presents a localization perception of a phantom sound image for ultrahigh-definition TV with respect to various loudspeaker configurations; two-horizontal, two-vertical and triplet loudspeakers. Vector base amplitude panning algorithm with modification for non-equidistant loudspeaker setup is applied to create the phantom sound image. In order to practically study the localization performance in real situation, the listening tests were conducted at the on-axis and off-axis positions of TV in normal listening room. A method of adjustment which can reduce the ambiguity of a perceived angle is exploited to evaluate the angles of octave-band signals. The subjects changed the panning angle until the real sound source and virtually panned source were coincident. A spatial blurring can be measured by examining the differences of the panning angles perceived with respect to each band. The listening tests show that the triplet panning method has better performance than vertical panning in view of perceptual localization and spatial blurring at both on-axis and off-axis positions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.207-209
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• 2021

In recent years, with the development of artificial intelligence and IoT technology, automation and unmanned technology are in progress in various fields, and the importance of image processing such as object tracking, medical images and object recognition, which are the basis of this, is increasing. In particular, in systems requiring detailed data processing, noise reduction is used as a pre-processing step, but the existing algorithm has a disadvantage that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using modified spatial weights to minimize information loss in the filtering process. The proposed algorithm uses mask matching to remove AWGN, and obtains the output of the filter by adding or subtracting the output of the modified spatial weight. The proposed algorithm has superior noise reduction characteristics compared to the existing method and reconstructs the image while minimizing the blurring phenomenon.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.115-124
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• 2005

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the problems. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the problems. As a result. the nearest neighbor interpolation. which is the most frequently applied algorithm for the existing image interpolation algorithm. shows that the identification of a magnified image is not possible. Therefore. this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson's curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter. this study will develop an interpolation algorithm that has an excel lent improvement for the boundary of the image and continuous and flexible property by using the NURBS. Ferguson's complex surface. and Bezier surface used in CAD/CAM engineering based on. the results of this study.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.2
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• pp.113-122
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• 2005

In this paper, we propose a multi-watermarking algorithm to satisfy two purposes: fragility against malicious attacks and robustness against non-malicious attacks. The algorithm can be used for image authentication using coefficients of Discrete Wavelet Transform(DWT). In the proposed method, watermarks are generated by combining binary image with some features extracted from the subband LL3, and then they are embedded into both the spatial and frequency domain. That is, on the spatial domain they are embedded into the Least Significant Bit(LSB) of all pixels of image blocks, and on the frequency domain the coefficients of the subband LH2 and HL2 are adjusted according to the watermarks. Thus the algorithm not only resists malicious attack but also permits non-malicious attacks such as blurring, sharpening, and JPEG compression.

• Journal of the Korean Society of Costume
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• v.58 no.8
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• pp.91-105
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• 2008

Spatial multiplication phenomenon, expressed through de-constructive trend since the late of 20C, have got changed existing fixed and dis-variable space to smooth, fluid, and changeable space. Ex-form and fluidity of new spatial paradigm have been focused through lots of scientific theories studied between digital thought and indeterminacy and rankless nature phenomena. In 21C fashion, indeterminate and irregular form and space have been crested continuously, which could not explain simply according as the fluidity theory Different from the space crested for multi-function and multipurpose, this is revealed the characteristics of chaosmos that communizes the order and the disorder, deconstruction and creation. Ex-formal space of fashion have shown the relationship of de-centerizing, de-territorial, and do-structural phenomenon among different fashion elements. This paper intends to understand the concept of ex-form, and study expressive manners of ex-formal space of 21C fashion, and conclusion as follows. 1) Overlap changes single space of fashion to multi-layered space through the repeat system of pleats, origami, and folding. 2) Ex-gravity expressed in deviation of the gravity acting vertical direction, for example, twisting, curve, winding, portion. 3) Morphing is shown the change process from single fixed form to different complex form. 4) Blurring is expressed in re-combination and re-arrangement among elements of fashion. 5) Blob shows hybrid fashion space through the liberal compounding and separation of a lot of different elements.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.332-339
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• 2014

Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

• ETRI Journal
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• v.46 no.2
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• pp.165-174
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• 2024

We propose a method to suppress the speckle noise and blur effects of the light field extracted from a hologram using a deep-learning technique. The light field can be extracted by bandpass filtering in the hologram's frequency domain. The extracted light field has reduced spatial resolution owing to the limited passband size of the bandpass filter and the blurring that occurs when the object is far from the hologram plane and also contains speckle noise caused by the random phase distribution of the three-dimensional object surface. These limitations degrade the reconstruction quality of the hologram resynthesized using the extracted light field. In the proposed method, a deep-learning model based on a generative adversarial network is designed to suppress speckle noise and blurring, resulting in improved quality of the light field extracted from the hologram. The model is trained using pairs of original two-dimensional images and their corresponding light-field data extracted from the complex field generated by the images. Validation of the proposed method is performed using light-field data extracted from holograms of objects with single and multiple depths and mesh-based computer-generated holograms.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.505-514
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• 2005

Image upsampling can be performed in both spatial and frequency (transform) domain. In the spatial domain, various upsampling techniques are developed and 6-tap FIR interpolation filter is most well known method, which is embedded in many video coding standards. It can provide high subjective quality but shows low objective quality. In the transform domain, simple zero padding method can produce upsampled image easily. It shows better objective quality than 6-tap filtering, but it yields ringing effects which annoy eyes. In this paper, we present efficient upsampling method using frequency addition method in transform domain to provide better subjective and objective quality than conventional method Extensive simulation results show that the proposed algorithm produces visually fine images with high PSNR.