• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2555-2575
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• 2017

This paper presents a dual exposure fusion method for image enhancement. Images taken with a short exposure time usually contain a sharp structure, but they are dark and are prone to be contaminated by noise. In contrast, long-exposure images are bright and noise-free, but usually suffer from blurring artifacts. Thus, we fuse the dual exposures to generate an enhanced image that is well-exposed, noise-free, and blur-free. To this end, we present a new scale-space patch-match method to find correspondences between the short and long exposures so that proper color components can be combined within a proposed dual non-local (DNL) means framework. We also present a residual filtering method that eliminates the structure component in the estimated noise image in order to obtain a sharper and further enhanced image. To this end, the entropy is utilized to determine the proper size of the filtering window. Experimental results show that our method generates ghost-free, noise-free, and blur-free enhanced images from the short and long exposure pairs for various dynamic scenes.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.462-470
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• 2008

This study applies fuzzy functions to improve image quality under the assumption that uncertainty of image information due to low contrast is based on vagueness and ambiguity of the brightness pixel values. To solve the problem of low contrast images whose brightness distribution is inclined, we use the k-means algorithm as a parameter of the fuzzy function, through which automatic critical points can be found to differentiate objects from background and contrast between bright and dark points can be improved. The fuzzy function is presented at the three main stages presented to improve image quality: fuzzification, contrast enhancement and defuzzification. To measure improved image quality, we present the fuzzy index and entropy index and in comparison with those of histogram equalization technique, it shows outstanding performance.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.4
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• pp.75-82
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• 2004

The channel transmission ratio is speeded up by the combination of the Huffman algorithm, the model scheme of the lossy transform having minimum average code lengths for the image information and good instantaneous decoding capability, with the Lempel-Ziv algorithm showing the fast processing performance during the compression process. In order to increase the processing speed during the compression process, ICMEP algorithm is proposed and the entropy encoder of HDTV is designed and inspected. The ICMEP entropy encoder have been designed by choosing the top-down method and consisted of the source codes and the test benches by the behavior expression with VHDL. As a simulation results, implemented ICMEP entropy encoder confirmed that whole system efficiency by memory saturation prevention and compressibility increase improves.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.1-8
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• 2010

The researches about gaze recognition which current user gazes and finds the location have increasingly developed to have many application. The gaze recognition of existence all about researches have got problems because of using equipment that Infrared(IR) LED, IR camera and head-mounted of high price. This study propose and implement the gaze recognition system based on SVM using a single PC Web camera. The proposed system that divide the gaze location of 36 per 9 and 4 to recognize gaze location of 4 direction and 9 direction recognize user's gaze. Also, the proposed system had apply on image filtering method using difference image entropy to improve performance of gaze recognition. The propose system was implements experiments on the comparison of proposed difference image entropy gaze recognition system, gaze recognition system using eye corner and eye's center and gaze recognition system based on PCA to evaluate performance of proposed system. The experimental results, recognition rate of 4 direction was 94.42% and 9 direction was 81.33% for the gaze recognition system based on proposed SVM. 4 direction was 95.37% and 9 direction was 82.25%, when image filtering method using difference image entropy implemented. The experimental results proved the high performance better than existed gaze recognition system.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.139-148
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• 2015

The purpose of image fusion is to combine the relevant information from a set of images into a single image, where the resultant fused image will be more informative and complete than any of the input images. Image fusion techniques can improve the quality and increase the application of these data important applications of the fusion of images include medical imaging, remote sensing, and robotics. In this paper, we suggest a new method to generate a fusion image using the close relation of image features obtained through maximum entropy threshold and mutual information. This method represents a good image registration in case of using a blurring image than other image fusion methods.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.29-32
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• 2008

In this paper, we propose one unsupervised classification technique using the degree of polarization (DoP) and the co-polarized phase-difference (CPD) statistics, instead of the entropy and alpha. It is shown that the DoP is closely related to the entropy, and the CPD to the alpha. The DoP explains the feature how much the effect of multiple reflections is contained. Hence, the DoP could be used as an important factor for classifying classes. The CPD can also be computed from the measured Mueller matrix elements. For the smooth surface scattering, the CPD is about $0^{\circ}$, and for dihedral-type scattering, the CPD is about $180^{\circ}$. A DoP-CPD diagram with appropriate boundaries between six different classes is developed based on the SAR image. The classification results are compared with the existing Entropy-alpha diagram as well as the IPL-AirSAR polarimetric data. The technique may have capability to classify an SAR image into six major classes; a bare surface, a village, a crown-layer short vegetation canopy, a trunk-layer short vegetation canopy, a crown-layer forest, and a trunk-dominated forest. Based on the DoP and CPD analysis, a simple three-component decomposition technique was also proposed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.4
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• pp.316-319
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• 2018

To detect the ground moving target, forward-looking SAR images obtained from the FMCW radar can be exploited. However, the quality of the SAR image is deteriorated due to the turbulence or fluctuation because of the flight path condition during the missile movement. We herein propose an entropy-minimizing autofocus method to compensate the motion error of forward-looking SAR. In particular, owing to the geometry of the forward-looking SAR, the motion error affects the SAR image in the two-dimensional (2D) form (azimuth and time axis). Therefore, we suggest a 2D autofocus method for the motion compensation.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.377-384
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• 2009

A new algorithm in order to classify various contents in the image documents, such as text, figure, graph, table, etc. is proposed in this paper by classifying contents using texture-based PCA, and by segmenting document images using local entropy-based histogram. Local entropy and histogram made the binarization of image document not only robust to various transformation and noise, but also easy and less time-consuming. And texture-based PCA algorithm for each segmented region was taken notice of each content in the image documents having different texture information. Through this, it was not necessary to establish any pre-defined structural information, and advantages were found from the fact of fast and efficient classification. The result demonstrated that the proposed method had shown better performances of segmentation and classification for various images, and is also found superior to previous methods by its efficiency.

• Journal of radiological science and technology
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• v.46 no.2
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• pp.89-97
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• 2023

With the introduction of the D.R system, the grid with high removal rate of scattered radiation is selected and used without considering the grid performance evaluation. Despite the high removal rate of scattered radiation belonging to high grid ratio, it is also possible to see the cut-off phenomenon in which the primary ray involved in the formation of image could be removed as well. Thus, the purpose of this study is to provide the basic data for researches on the usefulness of using the grid by presenting the appropriate grid ratio in the D.R system through the measurement of image in grid such as non-grid, 6:1, 8:1, 10:1, 12:1. The equipments used for this study were radiation generator with grid in 12:1, 10:1, 8:1, 6:1, indirect-type detector, and acryl phantom. As the study for image evaluation, this study measured the SNR, PSNR, MSE, and Entropy. In the results of this study, the PSNR was the highest in 6:1 and the lowest in 8:1. The SNR was high in 6:1 and 8:1, and the lowest in 12:1. In case of Entropy, it was high in 8:1 and 10:1, and the lowest in 12:1. Therefore, when the grid is used, it would be more proper to choose the grid in 8:1 or 10:1 with less loss in information content of primary ray rather than the high grid ratio showing the increased patient exposure dose.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.20-24
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• 1999

Grinding System is very difficult to examine closely wear phenomenon or dynamic characterastic because it is very complex and different from a general cutting system, Considering automatization and precision it is very important to examine closely grinding system. In this study grinding wheel surface is acquired by using computer vision system in order to explain wear and loading phenomenon. We investigate the relationship between wear and Fourier spectrum of acquired image and observe the entropy variation in the process of manufacturing.