• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1178-1188
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• 2003

In this paper, we describe image mosaicing techniques for constructing a large high-resolution image with images taken by a video camera in hand. we propose the method which is automatically retrieving the exact matching area using color information and shape information. The proposed method extracts first candidate areas which have similar form using a Voronoi Distance Matching Method which is rapidly estimating the correspondent points between adjacent images, and calculating initial transformations of them and finds the final matching area using color information. It is a method that creates Voronoi Surface which set the distance value among feature points and other points on the basis of each feature point of a image, and extracts the correspondent points which minimize Voronoi Distance in matching area between an input image and a basic image using the binary search method. Using the Levenberg-Marquadt method we turn an initial transformation matrix to an optimal transformation matrix, and using this matrix combine a basic image with a input image.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.237-240
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• 2001

본 논문은 단일 뷰-포인트 카메라 모델을 이용하여 무-특징 환경 (non-feature environment)에서의 영상 모자이킹 알고리즘을 제안한다. 특징 환경에서 영상의 기하구조를 만들어 내고 이 기하구조를 무-특징 환경에 적용시켜 모자이크 영상을 얻는다.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.49-56
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• 2009

Recently, a generation of high quality mosaic images from video sequences has been attempted by a variety of investigations. Among the matter of investigation, in this paper, generation on stereo mosaic utilizing airborne-video sequence images is focused upon. The stereo mosaic is made by creating left and right mosaic which are fabricated by front and rear slices having different viewing angle in consecutive video frames. For making the stereo mosaic, motion parameters which are able to define geometric relationship between consecutive video frames are determined. For determining motion parameters, affine model which is able to explain relative motion parameters is applied by this paper. The mosaicing method using relative motion parameters is called by free mosaic. The free mosaic proposed in this paper consists of 4 step processes: image registration with reference to first frame using affine model, front and rear slicing, stitching line definition and image mosaicing. As the result of experiment, the left and right mosaic image, anaglyphic image for stereo mosaic images are showed and analyzed y-parallax for checking accuracy.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.999-1000
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• 2008

Image Registration is used many works in image processing widely. But It is difficult to find the accuracy informations such as translation, rotation, and scaling between images. This paper proposes an algorithm that Fourier based image registration using the pyramid edge detection and line fitting. It can be estimated the informations by each sub-pixels. The proposed algorithm can be used for image registrations which high efficiency is required such as GIS, or MRI, CT, image mosaicing, weather forecasting, etc.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.415-418
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• 2001

The automatic construction of large, high-resolution image mosaics is an active area of reasearch in the fields of photogrammetry, computer vision, image processing, and computer graphics. In this study, we describe a automatic mosaicing method that makes a panorama from images by placing camera in a emitted-grid. In the images captured by cameras, there must be a matched area and the area is in the particular area of the image. Initial transformation matrix, there(ore, is calculated from points searched in the partial area. It is possible to find best transformation matrix by Levenberg-Marquardt method. Finally, each images are multiplied by blending function and stitched by the transformation matrix to complete panoramic image.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.393-396
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• 2000

본 논문에서는 영상의 화소값으로부터 추출된 유사 특징점(quasi-feature point)을 이용한 이미지 모자이킹 알고리즘을 제안한다. 유사 특징점의 선택은 전역 정합(global matching)의 결과로부터 중첩된 영역을 4개의 부영역(sub-area)으로 분할하고, 각각의 분할된 부 영역에서 국부 분산(local variance)의 크기가 큰 블록을 선정, 이 블록의 중심 화소를 유사 특징점으로 선택한다. 유사 특징점에 대한 정합은 카메라 이동에 따른 왜곡(distortion)과 조명의 변화를 고려한 블록 정합 알고리즘(block matching algorithm)을 이용한다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.381-384
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• 2000

본 논문은 움직임이나 장면에 제약되지 않는 카메라로부터 획득한 여러장의 디지털 영상을 한장의 통힙된 영상으로 자동적으로 모자이킹 하는 방법에 대해 기술한다. 우선 영상을 세그멘테이션과 레이블링으로 영상의 영역을 분할하고, 특징 점을 찾는다. 같은 영역으로 분할된 곳의 특징점을 각각의 그룹으로 하고 영역안의 특징점을 hausdorff distance를 이용영상을 비교하여 대응점을 구한 후 비선형 이승오차 최적화 알고리즘을 이용해 최적의 변환 행렬로 하나의 영상을 자동적으로 구성하는 과정에 대해서 기술한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.157-160
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• 2000

본 논문은 제약되지않은 카메라에서 얻은 영상중 회전과 크기 변화를 가진 두 장의 디지털 영상을 자동적으로 하나의 통합된 영상으로 모자이킹 하는 방법에 대해 기술한다. 기존에 제시되었던 영상 모자이킹 방법은 영상의 중첩 영역이 많이 존재하거나 회전이 거의 없는 경우만을 고려하고, 카메라 제약이 많이 존재하였다. 우선, 한 쌍의 영상으로부터 각각 특징점을 찾고, 각 특징 점에 대하여 위상을 측정하여 계층적으로 매칭을 하는 방법을 제안한다. 다음으로 비선형 이승오차 최적화 알고리즘을 이용해 최적의 변환행렬을 구한후 , 변환 행렬에 대해 하나의 영상을 만들어내는 과정을 기술한다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.423-425
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• 2003

In this paper, we propose a new scheme for matching specified areas in a satellite image, which is a very efficient method because it can be effectively applied to images that have various features. These features may include different spatial resolution and brightness; sometimes they may different geometrical property. The proposed method can be applied to some application fields such as mosaicing of satellite imagery, GCP matching.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.74-83
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• 2023

In this paper, we propose an image compression scheme which uses a demosaicking network and a channel-wise decoder in the decoding network. For the demosaicing network, we use as the input a colored mosaiced pattern rather than the well-known Bayer pattern. The use of a colored mosaiced pattern results in the mosaiced image containing a greater amount of information pertaining to the original image. Therefore, it contributes to result in a better color reconstruction. The channel-wise decoder is composed of multiple decoders where each decoder is responsible for each channel in the color image, i.e., the R, G, and B channels. The encoder and decoder are both implemented by wavelet based auto-encoders for better performance. Experimental results verify that the separated channel-wise decoders and the colored mosaic pattern produce a better reconstructed color image than a single decoder. When combining the colored CFA with the multi-decoder, the PSNR metric exhibits an increase of over 2dB for three-times compression and approximately 0.6dB for twelve-times compression compared to the Bayer CFA with a single decoder. Therefore, the compression rate is also increased with the proposed method than with the method using a single decoder on the Bayer patterned mosaic image.