• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.320-325
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• 2007

인간의 보다 질 높은 생활관을 추구하기 위하여 친 환경적인 산업개발 및 환경 복원 사업에 대한 노력이 최근 들어 끊임없이 지속되고 있다. 본 연구에서는 서울시 청계천을 대상으로 청계천 복원 전과 복원후의 지표 열 분포도를 작성하고 이를 기반으로 청계천 복원 전${\cdot}$후의 지표 열 변화를 분석하였다. 아울러 지표온도와 현지 관측 자료인 AWS 자료와의 비교 분석을 수행하여 지표온도와 대기온도 차를 도출하였다. ASTER 영상 열적외센서(TIR) 와 GIS 를 활용하여 도시 지표면의 온도를 추출하고, AWS 기 상관측자료와의 상관성 분석 함으로써 도심의 지역적 인 지표 열 패턴과 국지적인 기후연구에 활용가능성을 제시하고자 한다.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.770-783
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• 2012

In this paper, we propose a novel structure recovery algorithm in the projective space using image feature points. We use normalized image feature coordinates for the numerical stability. To acquire an initial value of the structure and motion, we decompose the scaled measurement matrix using the singular value decomposition. When recovering structure and motion in projective space, we introduce matrix decomposition constraints. In the reconstruction procedure, a nonlinear iterative optimization technique is used. Experimental results showed that the proposed method provides proper accuracy and the error deviation is small.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.91-99
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• 1994

We proposed the regularized iterative restoration method considering relaxation parameter and regularization paramenter in order to restore the noisy motion-blurred images. We used (i-H) as a regularization operator and these two kinds of constraints were applied while conventional regularization iterative restoration method proposed by Jan Biemond et al used the 2-D Laplacian filter and a predetermined regularization parameter value and relaxation parameter to 1. Through the experimental results, we showed better results compared with those by a conventional method and or regularized iterative restoration method just considering only a regularization parameter. These two kinds of constratints have good effects when applied into the regularized iterative restoration method for noisy motion-blurred images.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.925-928
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• 2006

본 논문에서는 영상에 워터마크를 삽입하고 추출하는 동시에 원영상을 복원하는 리버서블 워터마킹 알고리즘을 제안한다. 제안한 알고리즘의 핵심은 워터마크가 삽입된 영상에 변하지 않는 위치정보를 전달하는 것이다. 본 논문에서는 우선 원영상을 odd image와 even image로 분리한 다음odd image에 interpolation 기법을 이용하여 resizing시키고 resizing 된 영상(odd_resize_image)에서 기수항은 그대로 두고 우수항은 기수항과 우수항의 차이값으로 채우는 방법으로 location map을 얻는다. 이 location map 에 의해 워터마크를 삽입위치를 선택하면 추출과정에서도 같은 location map을 이용할 수 있기에 워터마크 삽입위치를 정확하게 판단하여 추출할 수 있고 동시에 원본 영상을 복원할 수 있다. 본 알고리즘은 영상에 변화를 적게 주었기 때문에 높은 비가시성을 보인다. 실험 결과 $256{\times}256$ 영상에서 PSNR이 평균 53.07dB의 우수한 비가시성을 보였다.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.595-600
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• 2008

본 논문에서는 위성영상 기반의 3차원 문화재 정보 시스템을 구현하기 위한 과정으로 고 해상 위성영상 제작을 위한 DEM(Digital Elevation Model)제작단계와 위성영상 자료를 수집하여 영상이 지니고 있는 왜곡을 보정하는 자료보정 단계, 사용 목적에 맞게 영상을 가공하여 저장하는 영상 생성단계를 통해 위성영상 기반의 3차원 지형정보를 생성하고, 3차원 스캐너를 활용한 대상지역 문화재의 DB 구축과 3차원 복원을 통해 3차원의 문화재 정보를 획득하고 질감 및 재질 사실적인 면을 강조하기 위한 텍스처 맵핑 과정을 통해 3차원 공간적인 조건 및 검색을 가능하게 함으로써 언제 어디서 든 누구나 쉽게 문화재에 대한 정보를 검색할 수 있도록 Web3D를 활용한 3차원 문화재 정보 시스템을 구현하였다.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.857-860
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• 2008

In this paper, we propose a removable logo watermarking technique for copyright protection of digital image. Then, visible logo is inserted into digital image to protect copyright, and the information removed by the logo is embedded by a new quantization watermarking. In a legal usage, the image can be reconstructed without logo after watermarking detection process. Experiment results show that the proposed method maintains high image quality in both watermarked images and reconstructed images, and is practical and effective in protection of image copyright.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.9
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• pp.952-958
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• 2014

In this paper, we propose a parametric sparse recovery algorithm(SRA) applied to a radar signal model, based on the compressive sensing(CS), for the ISAR(Inverse Synthetic Aperture Radar) image reconstruction from an incomplete radar-cross-section(RCS) data and for the estimation of rotation rate of a target. As the SRA, the iteratively-reweighted-least-square(IRLS) is combined with the radar signal model including chirp components with unknown chirp rate in the cross-range direction. In addition, the particle swarm optimization(PSO) technique is considered for searching correct parameters related to the rotation rate. Therefore, the parametric SRA based on the IRLS can reconstruct ISAR image and estimate the rotation rate of a target efficiently, although there exists missing data in observed RCS data samples. The performance of the proposed method in terms of image entropy is also compared with that of the traditional interpolation methods for the incomplete RCS data.

• Korean Journal of Digital Imaging in Medicine
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• v.4 no.1
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• pp.182-189
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• 1998

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.127-135
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• 2006

The image-based 3D modeling is the technique of generating a 3D graphic model from images acquired using cameras. It is being researched as an alternative technique for the expensive 3D scanner. In this paper, I propose the image-based 3D modeling system using calibrated camera. The proposed algorithm for rendering 3D model is consisted of three steps, camera calibration, 3D shape reconstruction and 3D surface generation step. In the camera calibration step, I estimate the camera matrix for the image aquisition camera. In the 3D shape reconstruction step, I calculate 3D volume data from silhouette using pyramidal volume intersection. In the 3D surface generation step, the reconstructed volume data is converted to 3D mesh surface. As shown the result, I generated relatively accurate 3D model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.112-122
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• 2009

In this paper, we present a novel space-frequency adaptive image restoration approach using vaguelette-wavelet decomposition (VWD). The proposed algorithm classifies a degraded image into flat and edge regions by using spatial information of the wavelet coefficient. For reducing the noise we perform an adaptive wavelet shrinkage process. At edge region candidates, we adopt entropy approach for estimating the noise and remove it by using relative between sub-bands. After shrinking wavelet coefficients process, we restore the degraded image using the VWD. The proposed algorithm can reduce the noise without affecting the sharpness details. Based on the experimental results, the proposed algorithm efficiently proved to be able to restore the degraded image while preserving details.