• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.517-528
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• 2007

Extraction of the coastal boundary is important because the boundary serves as a reference in the demarcation of maritime zones such as territorial sea, contiguous zone, and exclusive economic zone. Accurate nautical charts also depend on well established, accurate, consistent, and current coastline delineation. However, to identify the precise location of the coastal boundary is a difficult task due to tidal and wave motions. This paper presents an efficient way to extract coastlines by applying digital image processing techniques to Synthetic Aperture Radar (SAR) imagery. Over the past few years, satellite-based SAR and high resolution airborne SAR images have become available, and SAR has been evaluated as a new mapping technology. Using remotely sensed data gives benefits in several aspects, especially SAR is largely unaffected by weather constraints, is operational at night time over a large area, and provides high contrast between water and land areas. Various image processing techniques including region growing, texture-based image segmentation, local entropy method, and refinement with image pyramid were implemented to extract the coastline in this study. Finally, the results were compared with existing coastline data derived from aerial photographs.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.11
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• pp.1154-1166
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• 1991

Optical flow is important not only for determining velocity and trajectory of the object but also for image segmentation and three dimensional information. In this paper an algorithm for segmentation of the optical flow field is presented. This method is based on a pyramid linking method combined with the proposed models. In this method each node contained a model of the flow in the region that it represented regions were combined by taking the model that best fit the union of the two regions. Each node linked to one of its fathers based on the error between the pixels represented by the node and the father's model of its flow. A major problem which has emerged in conventional researchs on optical flow field is sensitive to noise the proposed method is relatively insensitive to noise at the result of computer simulation the pyramid algorithm proposed in this paper seem to have useful properties.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.150-153
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• 2001

라플라시안 피라미드 영상을 효율적으로 구성하기 위하여 3$\times$3 가중치 행렬을 이용한 가우시안 저역파기를 이용한다. 각 단계의 영상 전송 시 해당 부호화 방법은 엔트로피 부호화 방법 중 무기억 정보원을 이용하는 허프만 부호화와 산술 부호화 기법을 사용한다. 또한, 기억 정보원을 이용하는 1중 마르코프 산술 부호화를 사용한다. 1중 마르코프 산술 부호화를 사용하면 하위단계 영상일 수록 압축이 더 효율적임을 시뮬레이션을 통하여 보인다.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.175-178
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• 2000

인접한 화소들간의 상관성에 대한 오류 정보만을 추출하여 전송하는 기법인 라플라시안 피라미드는 알고리즘 구성이 간단하며, 낮은 엔트로피 전송이 가능한 무손실 예측 압축과 점진적인 전송이 가능한 이점을 가지고 있다. 이러한 라플라시안 피라미드를 효율적으고 구성하기 위하여 기존의 5$\times$5 가중치 행렬을 3$\times$3 가중치 행렬로 구성하는 새로운 기법을 보인다. 3$\times$3 가중치행렬을 이용하는 방법이 5$\times$5 가중치 행렬에 의한 알고리즘의 구성보다 간단하면서도 압축효율이 좋음을 시뮬레이션을 통하여 보인다.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.647-650
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• 1988

This paper proposes and sketches out a new parallel architecture of transputer-based pyramidal parallel array computer (TPPAC) used to process computationally intensive problems for geometric processing applications such as computer vision, image processing etc. It explores how efficiently the pyramid computer architecture is designed using transputer chips, and poses a new interconnection scheme for TPPAC without using additional transputers.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.3
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• pp.8-14
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• 2012

Improving the speed of image processing is in great demand according to spread of high quality visual media or massive image applications such as 3D TV or movies, AR(Augmented reality). SIMD computer attached to a host computer can accelerate various image processing and massive data operations. MAMS is a multi-access memory system which is, along with multiple processing elements(PEs), adequate for establishing a high performance pipelined SIMD machine. MAMS supports simultaneous access to pq data elements within a horizontal, a vertical, or a block subarray with a constant interval in an arbitrary position in an $M{\times}N$ array of data elements, where the number of memory modules(MMs), m, is a prime number greater than pq. MAMS-PP4 is the first realization of the MAMS architecture, which consists of four PEs in a single chip and five MMs. This paper presents implementation of image processing algorithms and performance analysis for MAMS-PP16 which consists of 16 PEs with 17 MMs in an extension or the prior work, MAMS-PP4. The newly designed MAMS-PP16 has a 64 bit instruction format and application specific instruction set. The author develops a simulator of the MAMS-PP16 system, which implemented algorithms can be executed on. Performance analysis has done with this simulator executing implemented algorithms of processing images. The result of performance analysis verifies consistent response of MAMS-PP16 through the pyramid operation in image processing algorithms comparing with a Pentium-based serial processor. Executing the pyramid operation in MAMS-PP16 results in consistent response of processing time while randomly response time in a serial processor.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.431-447
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• 2021

Recently, the use of high-resolution satellites is increasing in many areas. In order to supply useful satellite images stably, it is necessary to establish automatic precision geometric correction technic. Geometric correction is the process that corrected geometric errors of satellite imagery based on the GCP (Ground Control Point), which is correspondence point between accurate ground coordinates and image coordinates. Therefore, in the automatic geometric correction process, it is the key to acquire high-quality GCPs automatically. In this paper, we proposed iterative precision geometry correction method. we constructed an image pyramid and repeatedly performed GCP chip matching, outlier detection, and precision sensor modeling in each layer of the image pyramid. Through this method, we were able to acquire high-quality GCPs automatically. we then improved the performance of geometric correction of high-resolution satellite images. To analyze the performance of the proposed method, we used KOMPSAT-3 and 3A Level 1R 8 scenes. As a result of the experiment, the proposed method showed the geometric correction accuracy of 1.5 pixels on average and a maximum of 2 pixels.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1901-1910
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• 2022

Arriving in the new space age, securing technology for fusion application of KOMPSAT-3·3A and global satellite images is becoming more important. In general, multi-sensor satellite images have relative geometric errors due to various external factors at the time of acquisition, degrading the quality of the satellite image outputs. Therefore, we propose a fine-image registration methodology to minimize the relative geometric error between KOMPSAT-3·3A and global satellite images. After selecting the overlapping area between the KOMPSAT-3·3A and foreign satellite images, the spatial resolution between the two images is unified. Subsequently, tie-points are extracted using a hybrid matching method in which feature- and area-based matching methods are combined. Then, fine-image registration is performed through iterative registration based on pyramid images. To evaluate the performance and accuracy of the proposed method, we used KOMPSAT-3·3A, Sentinel-2A, and PlanetScope satellite images acquired over Daejeon city, South Korea. As a result, the average RMSE of the accuracy of the proposed method was derived as 1.2 and 3.59 pixels in Sentinel-2A and PlanetScope images, respectively. Consequently, it is considered that fine-image registration between multi-sensor satellite images can be effectively performed using the proposed method.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.99-110
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• 1997

Image matching to determine the conjugate points in stereo photos is the one of the most important subject in digital photogrammetry and many researches In digital photogrammetric field are on going to automate the image matching process. In this study, we analyzes the effect of allowable correlation coefficient, which controls the accuracy in areal based image matching, on the accuracy of digital photogrammetry. So, some areal based matching methods such as image correlation coefficient matching, image Pyramid matching and interest point matching, are implemented, and the effect of allowable correlation coefficient on accuracy of digital photogrammetry in each method is analyzed. As a result of this study, a method to determine the optimal correlation coefficient is presented.