• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.06a
• /
• pp.255-256
• /
• 2019

본 논문에서는 초고해상도 기술의 복잡도를 줄이기 위하여 픽셀단위 생략 방법을 제안한다. 제안하는 방법은 픽셀 단위로 수평, 수직 방향의 밝기에 대한 2 차 미분치에 기반하여 생략을 결정한다. 제안하는 방법의 성능 평가를 위하여 가장 간단한 초고해상도 알고리즘인 SRCNN 과 제안하는 방법의 PSNR 비교한다. 그 결과 제안하는 방법이 평균적으로 약 47%의 픽셀이 생략이 되면서 SRCNN 대비 0.2dB PSNR 감소를 보인다.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.5
• /
• pp.9-17
• /
• 2008

This paper proposes a method of color reproduction considering the viewing conditions of a PDP TV. Because of a change of peripheral environments by a temporal and spatial location of observers, the ambient lightings should be considered in the process of color reproduction of displays. A conventional method enhances the contrast and saturation of images by controlling voltage gains in each channel, so that there is a limit to implementing the phenomenon of human adaptation. This method also faces difficulties in reproducing the perceived colors under a variety of viewing conditions. Accordingly, in order to solve this problem, we first characterize the device by considering the brightness and the flare effect. The chromatic adaptation is finally applied to reproduce colors in a PDP TV using the information from the viewing conditions by the sensor. The images reproduced by the proposed method are visually more superior to those reproduced by a conventional method in the experiments.

• Korean Journal of Remote Sensing
• /
• v.30 no.6
• /
• pp.769-776
• /
• 2014

It is necessary to detect the feature points existing simultaneously in both images and then find the corresponding relationship between the detected feature points. We propose a new feature detector based on geometric mean of two eigenvalues of gradient matrix which is able to measure the change of pixel intensities. The corner response of the proposed detector is proportional to the geometric mean and also the difference of two eigenvalues in the case of same geometric mean. We analyzed the localization error of the feature detection using aerial image and artificial image with various types of corners. The localization error of the proposed detector was smaller than that of the typical corner detector, Harris detector.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.5
• /
• pp.663-674
• /
• 1993

In this paper, a DCT image coding algorithm using the human visual property is proposed. Human visual is relatively sensitive to noise in the darker region, insensitive to noise in the brighter region. This property was proved by Weber's law through psycovisual experiment. Weber's law states that the just noticeable difference (j.n.d.) is proportional to intensity. Therefore, the implication of this observation for image processing is that reducing noise in the darker region is more important than reducing noise in the brighter region. In this proposed coding scheme AC coefficients in the darker region are more finely quantized than those in the brighter region. Results showed that, at low bit rate, the subjective quality of reconstructed images by proposed coding scheme is improved than that of coding scheme without considering human visual property.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.10 no.2
• /
• pp.57-62
• /
• 1992

As population is increased, land use types are changed mountainous areas from flatland in Korea. Because natural disaster as landslides occur of life, property, and environmental damage, prediction of landslides have become increasingly important. We focus on the issue for assessment of landslides, not slope stability analysis for a simple slope site. In this study, we could know the correlations of mean, standard deviation for brightness value of imagery by aerial photo scanning. The range of brightness values and standard deviation of landslide area is 35~65 and tend to increment of value, in the every years. When evaluating large regions with past occurrence of landslides, it is possible to search for correlation of site conditions such as degree of slope, soil characteristics, vegetative cover, and rainfall conditions in aerial photo interpretation data.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.4
• /
• pp.16-22
• /
• 2009

In this paper, we propose an auto gain/offset which considers the visibility of human visual system (HVS) and the histogram of a target image jointly. In the proposed method, the lower and upper clipping thresholds are determined to maximize the averaged visibility of the contrast-stretched image. The target image is then contrast-stitched by the gain and offset derived from the clipping thresholds. We define the visibility as a quantity related to the spatial JND, which means the threshold below which any change of a pixel from its textured neighbors is not recognized by the HVS. Experimental results show that the contrast-stretched images by the proposed method have better global and local contrasts compared to the results by some conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.8
• /
• pp.1919-1925
• /
• 2013

This paper proposes a background image extraction algorithm for traffic environment analysis in a school zone. The proposed algorithm solves the problems by level changes and stationary objects to be occurred frequently in traffic environment. For the former, it renews rapidly the background image toward the current frame using a fast Sima-Delta algorithm and for the latter, it excludes the stationary objects from the background image by detecting dynamic regions using a just previous frame and a background image averaged for a long time. The results of experiments show that the proposed algorithm adapts quickly itself to level change well, and reduces about 40~80% of SAD in background region in comparison with the conventional algorithms.

• Journal of Korea Multimedia Society
• /
• v.16 no.12
• /
• pp.1376-1384
• /
• 2013

In this paper, we propose an automaticdetection method of foreign bodies through template matching in industrial CT volume data. Our method is composed of three main steps. First,Indown-sampling data, the product region is separated from background after noise reduction and initial foreign-body candidates are extracted using mean and standard deviation of the product region. Then foreign-body candidates are extracted using K-means clustering. Second, the foreign body with different intensity of product region is detected using template matching. At this time, the template matching is performed by evaluating SSD orjoint entropy according to the size of detected foreign-body candidates. Third, to improve thedetection rate of foreign body in original volume data, final foreign bodiesare detected using percolation method. For the performance evaluation of our method, industrial CT volume data and simulation data are used. Then visual inspection and accuracy assessment are performed and processing time is measured. For accuracy assessment, density-based detection method is used as comparative method and Dice's coefficient is measured.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.11C
• /
• pp.1140-1151
• /
• 2003

This paper proposes a face recognition method based on modified Otsu's binarization and Hu moment. Proposed method is robust to brightness, contrast, scale, rotation, and translation changes. As the proposed modified Otsu's binarization computes other thresholds from conventional Otsu's binarization, namely we create two binary images, we can extract higher dimensional feature vector. Here the feature vector has properties of robustness to brightness and contrast changes because the proposed method is based on Otsu's binarization. And our face recognition system is robust to scale, rotation, and translation changes because of using Hu moment. In the perspective of brightness, contrast, scale, rotation, and translation changes, experimental results with Olivetti Research Laboratory (ORL) database and the AR database showed that average recognition rates of conventional well-known principal component analysis (PCA) are 93.2% and 81.4%, respectively. Meanwhile, the proposed method for the same databases has superior performance of the average recognition rates of 93.2% and 81.4%, respectively.

• Korean Journal of Optics and Photonics
• /
• v.10 no.1
• /
• pp.32-39
• /
• 1999

In this paper, we made CGH patterns that had continuous amplitude distribution binary coded patterns with two different methods, and analyzed those patterns by using LCSLM (liquid crystal spatial light modulator). The error diffusion algorithm and direct quantization method were used as the binarization methods. The parameters of overall average brightness, mean square error, and diffraction efficiency were used in the comparison of reconstruction characteristics. The LCSLM which we used in this experiment was a binary reflective ferroelectric liquid crystal spatial light modulator addressed electrically with 256$\times$256 pixels, 87% fill factor and 15$\mu$m pixel pitch.