• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.215-216
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• 2007

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.65-77
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• 2014

To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3397-3413
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• 2016

Considering that the layered cellular automata (LCA) are naturally fit for representing image data in various applications, a novel reverse iterative image encryption scheme based on LCA is proposed. Specifically, the plain image is set as the final configuration of an 8-layer CA, and some sequences derived from a random sequence are set as the pre-final configuration, which ensure that the same plain image will never be encrypted in the same way when encrypted many times. Then, this LCA is backward evolved by following some reversible two order rules, which are generated with the aid of a newly defined T-shaped neighborhood. The cipher image is obtained from the recovered initial configuration. Several analyses and experimental results show that the proposed scheme possesses a high security level and executive performance.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.1-13
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• 2021

In this research, we study the problem of font image skeletonization using an end-to-end deep adversarial network, in contrast with the state-of-the-art methods that use mathematical algorithms. Several studies have been concerned with skeletonization, but a few have utilized deep learning. Further, no study has considered generative models based on deep neural networks for font character skeletonization, which are more delicate than natural objects. In this work, we take a step closer to producing realistic synthesized skeletons of font characters. We consider using an end-to-end deep adversarial network, SkelGAN, for font-image skeletonization, in contrast with the state-of-the-art methods that use mathematical algorithms. The proposed skeleton generator is proved superior to all well-known mathematical skeletonization methods in terms of character structure, including delicate strokes, serifs, and even special styles. Experimental results also demonstrate the dominance of our method against the state-of-the-art supervised image-to-image translation method in font character skeletonization task.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.643-649
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• 2016

This paper presents a new image cache algorithm for real-time implementation of high-resolution color image warping. The cache memory is divided into four cache memory modules for simultaneous readout of four input image pixels in consideration of the color filter array (CFA) pattern of an image sensor and CFA image warping. In addition, a pipeline structure from the cache memory to an interpolator is shown to guarantee the generation of an output image pixel at each system clock cycle. The proposed image cache algorithm is applied to an FPGA-based real-time color image warping, and experimental results are presented to show the validity of the proposed method.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.275-288
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• 2023

Many image edge details are easily lost in the image denoising process, and the smooth image regions are prone to produce jagged. In this paper, we propose a wavelet-based image global k- singular value decomposition variational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noise of low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes the random noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value is higher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that the proposed method can effectively suppress image noise while retaining more image edge details. The denoised image has better denoising effects.

• Progress in Medical Physics
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• v.20 no.4
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• pp.199-207
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• 2009

It is important to initialize Image Plate (IP) completely for removing residual latent image by sodium lamp for reliability and repeatability of computed radiography (CR) system. The purpose of this study was to evaluate latent images of computed radiography (CR) images respect to delay time after erasure of foregone latent image and its effect, and erasure level. Erasure thoroughness for CR acceptance test from American Association of Physicist in Medicine (AAPM) Report 93 (2006) was also evaluated. Measurements were made on a CR (Agfa CR 25; Agfa, BELGIUM) system. Chest postero-anterior (PA), Hand PA, L-spine lateral radiographs were chosen for evaluation. Chest phantom (3D-torso; CIRS, USA) was used for Chest PA and L-spine lateral radiography. For Hand PA radiography, projections was done without phantom. Except Hand PA radiographs, noise was increased with delay time, and ghost image was appeared on overexposed area. Effect of delay after erasure on latent image was not seen on naked eye, but standard deviation (SD) of pixel value on overexposed area was relatively higher than that of other areas. On Hand PA and Chest PA radiographs, noise were not occurred by adjustment of erasure level. On L-spine lateral images at lower erasure level than standard level, noise including ghost image were occurred because of high tube current. Erasure thoroughness of CR system in our department was to be proved by these evaluation. The results of this study could be used as a baseline for IP initialization and reliability of CR images.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.35-44
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• 2015

The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

• Journal of Information Display
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• v.8 no.3
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• pp.29-33
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• 2007

The temporal dark image sticking phenomena are examined and compared for the two different electrode structures such as the face-to-face and coplanar sustain electrode structure. To compare the temporal dark image sticking phenomena for both structures, the differences in the infrared emission profile, luminance, and perceived luminance of the image sticking cells and the non image sticking cells were measured. It is observed that the temporal dark image sticking is mitigated for the face-to-face structure. The mitigation of the temporal dark image sticking for the face-to-face structure is due to the slight increase in the panel temperature induced by the ITO-less electrode structure.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.321-326
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• 2013

The modulation transfer function (MTF) is a widely used indicator in assessments of remote-sensing image quality. This MTF method is also used to restore information to a standard value to compensate for image degradation caused by atmospheric or satellite jitter effects. In this study, we evaluated MTF values as an image quality indicator for the Geostationary Ocean Color Imager (GOCI). GOCI was launched in 2010 to monitor the ocean and coastal areas of the Korean peninsula. We evaluated in-orbit MTF value based on the GOCI image having a 500-m spatial resolution in the first time. The pulse method was selected to estimate a point spread function (PSF) with an optimal natural target such as a Seamangeum Seawall. Finally, image restoration was performed with a Wiener filter (WF) to calculate the PSF value required for the optimal regularization parameter. After application of the WF to the target image, MTF value is improved 35.06%, and the compensated image shows more sharpness comparing with the original image.