• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.28-37
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• 2001

An image retrieval method combining shape information of 2-dimension color histograms with color information of HSI color histograms is proposed in this paper. In addition, the proposed method can find location information of image through the comparison of similarity among subimages. The suggested retrieval method applies the location information to shape and color information and can retrieve region information which is hard to distinguish in the binary image. Some simulation results show that it works very well in the behalf of precision/recall graph compare with conventional method which uses color histogram. Especially, the proposed method brought well effects such as rotations and transitions of the objects in an image was found.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.825-828
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• 2006

The most commonly used techniques for image magnification are interpolation based. However, the magnified images produced by this technique often appear blocking and blurring phenomenon when the image is enlarged. In this paper, we enhanced image magnification algorithm using edge information. The proposed algorithm not used interpolation based but by using sub-band of input image in extrapolation. According to mapping relationship in pyramid, we calculated up-band information to magnify. In experiments, the proposed model shows solved the problem of image loss like the blocking and blurring phenomenon. As the result, it is faster and higher resolution than traditional magnification algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.1-12
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• 2005

Image registration is a process to establish the spatial correspondence between images of the same scene, which are acquired at different view points, at different times, or by different sensors. This paper presents a new algorithm for robust registration of the images acquired by multiple sensors having different modalities; the EO (electro-optic) and IR(infrared) ones in the paper. The two feature-based and intensity-based approaches are usually possible for image registration. In the former selection of accurate common features is crucial for high performance, but features in the EO image are often not the same as those in the R image. Hence, this approach is inadequate to register the E0/IR images. In the latter normalized mutual Information (nHr) has been widely used as a similarity measure due to its high accuracy and robustness, and NMI-based image registration methods assume that statistical correlation between two images should be global. Unfortunately, since we find out that EO and IR images don't often satisfy this assumption, registration accuracy is not high enough to apply to some applications. In this paper, we propose a two-stage NMI-based registration method based on the analysis of statistical correlation between E0/1R images. In the first stage, for robust registration, we propose two preprocessing schemes: extraction of statistically correlated regions (ESCR) and enhancement of statistical correlation by filtering (ESCF). For each image, ESCR automatically extracts the regions that are highly correlated to the corresponding regions in the other image. And ESCF adaptively filters out each image to enhance statistical correlation between them. In the second stage, two output images are registered by using NMI-based algorithm. The proposed method provides prospective results for various E0/1R sensor image pairs in terms of accuracy, robustness, and speed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.4
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• pp.359-365
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• 2004

Data integration techniques are becoming increasing1y important for conquering a limitation with a single data. Image fusion which improves the spatial and spectral resolution from a set of images with difffrent spatial and spectral resolutions, and image registration which matches two images so that corresponding coordinate points in the two images correspond to the same physical region of the scene being imaged have been researched. In this paper, we compared with six image fusion methods(Brovey, IHS, PCA, HPF, CN, and MWD) with panchromatic and multispectral images of IKONOS and developed the registration method for applying to SPOT-5 satellite image and RADARSAT SAR satellite image. As the result of tests on image fusion and image registration, we could find that MWD and HPF methods showed the good result in term of visual comparison analysis and statistical analysis. And we could extract patches which depict detailed topographic information from SPOT-5 and RADARSAT and obtain encouraging results in image registration.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.185-188
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• 2005

영상 기반 렌더링에서 평면에 투영된 사영 영상만을 가지고 3 차원 영상을 재구성 하는 여러 가지 모델링 기법들이 연구되어 왔다. 4D Plenoptic Function 을 사용하는 Light Field Rendering 이나 Lumigraph 방법은 여러 개의 영상으로 새로운 시점의 영상을 생성하는 기법이다. 이러한 방법은 사용자가 가상 세계에서의 항해를 가능하게 하고 2 차원의 정보만으로 3 차원 환경을 구성 할 수 있다. Concentric Mosaic, Plenoptic Stitching, Sea of Image 등은 Light Field 를 이용하여 사용자가 여러 가지 환경에서 항해할 수 있게 하는 기법이다. 특히 Takahashi 는 도시의 거리와 같은 대규모 환경에서의 항해에 관한 연구를 발표하였다. 단일 경로를 따라 파노라마 영상을 획득한 다음 Light Field 방법을 사용해서 새로운 시점의 영상을 생성한다. 하지만 대규모 환경에서 사용자가 이동할 수 있는 경로의 범위는 매우 넓고 경로를 따라 조밀하게 파노라마 영상을 획득해야 하기 때문에 데이터의 양이 많아지고 영상획득의 어려움이 있다. 이러한 단점으로 인하여 참조 영상의 네트워크 전송 시에 네트워크의 부하가 증가될 수 있다. 본 논문에서는 Takahashi 의 방법을 기본으로 파노라마 영상 모핑 방법을 이용하여 임의 시점 (Arbitrary View)의 영상을 렌더링 하는 방법을 제안한다. 파노라마 영상의 획득 간격을 비교적 크게 하면서 파노라마 영상 모핑 기법을 이용하여 중간 영상을 생성한 후 Takahashi 의 방법을 사용하여 임의 영상을 생성하는 방법이다. 적은 수의 파노라마 영상으로 비교적 좋은 임의 시점의 영상을 재구성 할 수 있었다.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.319-326
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• 2002

In this paper, we have designed and implemented cluttering classification systems- unsupervised classifiers-for the processing of satellite remote sensing images. Implemented systems adopt various design patterns which include a factory pattern and a strategy pattern to support various satellite images'formats and to design compatible systems. The clustering systems consist of sequential clustering, K-Means clustering, ISODATA clustering and Fuzzy C-Means clustering classifiers. The systems are tested by using a Landsat TM satellite image for the classification input. As results, these clustering systems are well designed to extract sample data for the classification of satellite images of which there is no previous knowledge. The systems can be provided with real-time base clustering tools, compatibilities and components' reusabilities as well.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.26-32
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• 2009

In the satellite image fusion, the most important point is to preserve both the spatial detail of panchromatic(PAN) image and the spectral information of multispectral(MS) image. Among various image fusion techniques, fusion technique using Intensity-Hue-Saturation(IHS) transform is widely used and it has advantage that computation is very simple. In this study, a fusion technique using fast IHS transform and trade-off parameter $\alpha^i$ proposed. Proposed fusion technique permits customization of the trade-off between the spectral information and spatial detail quality of the fused image through the evaluation of two quality indices: a spectral index(the spectral ERGAS) and a spatial one(the spatial ERGAS). Based on the result of experiment using IKONOS image, we confirmed the proposed fusion technique was more effective in preserving spatial detail and spectral information than existing fusion techniques using fast IHS transform.

• Progress in Medical Physics
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• v.24 no.2
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• pp.99-107
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• 2013

The surgical resection was occurred mainly in liver metastasis before the development of radiation therapy techniques. Recently, Radiation therapy is increased gradually due to the development of radiation dose delivery techniques. 18F-FDG PET image showed better sensitivity and specificity in liver metastasis detection. This image modality is important in the radiation treatment with planning CT for tumor delineation. In this study, we applied automatic image segmentation methods on PET image of liver metastasis and examined the impact of image factors on these methods. We selected the patients who were received the radiation therapy and 18F-FDG PET/CT in Korea Cancer Center Hospital from 2009 to 2012. Then, three kinds of image segmentation methods had been applied; The relative threshold method, the Gradient method and the region growing method. Based on these results, we performed statistical analysis in two directions. 1. comparison of GTV and image segmentation results. 2. performance of regression analysis for relation between image factor affecting image segmentation techniques. The mean volume of GTV was $60.9{\pm}65.9$ cc and the $GTV_{40%}$ was $22.43{\pm}35.27$ cc, and the $GTV_{50%}$ was $10.11{\pm}17.92$ cc, the $GTV_{RG}$ was $32.89{\pm}36.8$4 cc, the $GTV_{GD}$ was $30.34{\pm}35.77$ cc, respectively. The most similar segmentation method with the GTV result was the region growing method. For the quantitative analysis of the image factors which influenced on the region growing method, we used the standardized coefficient ${\beta}$, factors affecting the region growing method show GTV, $TumorSUV_{MAX/MIN}$, $SUV_{max}$, TBR in order. The result of the region growing (automatic segmentation) method showed the most similar result with the CT based GTV and the region growing method was affected by image factors. If we define the tumor volume by the auto image segmentation method which reflect the PET image parameters, more accurate and consistent tumor contouring can be done. And we can irradiate the optimized radiation dose to the cancer, ultimately.

• Tunnel and Underground Space
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• v.12 no.1
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• pp.1-9
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• 2002

Recently, the use of image analysis methods and commercial equipments has been extensively increased in the field of rock engineering. However the problem of errors involved in the image acquisition and subsequent analysis procedure has been frequently neglected. In addition there has been few studies dealing with this problem. So proper color calibration method is needed to be developed for the objectivity and improvement of reliability on image analysis of rock. Color calibration method using standard color rendition chart was adopted on this study. Color calibration and error analysis were carried out for the image acquired from granite rock samples. As a result, comparison among other rock images and improvement of reliability on whole analysis were possible.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.41-48
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• 2012

Using multi-sensor or multi-temporal high resolution satellite images together is essential for efficient applications in remote sensing area. The purpose of this paper is to estimate geometric difference of translations between high-resolution optical and SAR images automatically. The geometric and radiometric pre-processing steps were fulfilled to calculate the similarity between optical and SAR images by using Mutual Information method. The coarsest-level pyramid images of each sensor constructed by gaussian pyramid method were generated to estimate the initial translation difference of the x, y directions for calculation efficiency. The precise geometric difference of translations was able to be estimated by applying this method from coarsest-level pyramid image to original image in order. Yet even when considered only translation between optical and SAR images, the proposed method showed RMSE lower than 5m in all study sites.