• Title/Summary/Keyword: Mosaic images

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Video Mosaic System by Multi-Image (다중 영상에 의한 비디오 모자이크 시스템)

  • 양원보;임문순;이양원
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.05a
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    • pp.104-108
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    • 1999
  • It is presented many effect that represented by implicated one image more than each images with a fragment meaning. ‘Mosaic’ is technique be applied at this situation. ‘Mosaic’ is created by complicated one new image which by multi image be eliminated overlap region. This research is development for mosaic system by multi image. The system is divided that shot segmentation and mosaic image creation. Shot segmentation divided that merge with respect to similarity images which video data of moving picture in sequence time and mosaic image creation is composed of one image with which all frames in segmented shot.

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Multi-temporal Landsat ETM+ Mosaic Method for Generating Land Cover Map over the Korean Peninsula (한반도 토지피복도 제작을 위한 다시기 Landsat ETM+ 영상의 정합 방법)

  • Kim, Sun-Hwa;Kang, Sung-Jin;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.87-98
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    • 2010
  • For generating accurate land cover map over the whole Korean Peninsula, post-mosaic classification method is desirable in large area where multiple image data sets are used. We try to derive an optimal mosaic method of multi-temporal Landsat ETM+ scenes for the land cover classification over the Korea Peninsula. Total 65 Landsat ETM+ scenes were acquired, which were taken in 2000 and 2001. To reduce radiometric difference between adjacent Landsat ETM+ scenes, we apply three relative radiometric correction methods (histogram matching, 1st-regression method referenced center image, and 1st-regression method at each Landsat ETM+ path). After the relative correction, we generated three mosaic images for three seasons of leaf-off, transplanting, leaf-on season. For comparison, three mosaic images were compared by the mean absolute difference and computer classification accuracy. The results show that the mosaic image using 1st-regression method at each path show the best correction results and highest classification accuracy. Additionally, the mosaic image acquired during leaf-on season show the higher radiance variance between adjacent images than other season.

Development of Brightness Correction Method for Mosaicking UAV Images (무인기 영상 병합을 위한 밝기값 보정 방법 개발)

  • Ban, Seunghwan;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1071-1081
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    • 2021
  • Remote Sensing using unmanned aerial vehicles(UAV) can acquire images with higher time resolution and spatial resolution than aerial and satellite remote sensing. However, UAV images are photographed at low altitude and the area covered by one image isrelatively narrow. Therefore multiple images must be processed to monitor large area. Since UAV images are photographed under different exposure conditions, there is difference in brightness values between adjacent images. When images are mosaicked, unnatural seamlines are generated because of the brightness difference. Therefore, in order to generate seamless mosaic image, a radiometric processing for correcting difference in brightness value between images is essential. This paper proposes a relative radiometric calibration and image blending technique. In order to analyze performance of the proposed method, mosaic images of UAV images in agricultural and mountainous areas were generated. As a result, mosaic images with mean brightness difference of 5 and root mean square difference of 7 were avchieved.

The Study on an Advanced Algorithm for Auto-generation of MOSAIC Seam Lines

  • Park, Young-Hoon;Kim, Jin-Kwang;Kang, Young-Ku
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.464-466
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    • 2003
  • In this paper an advanced algorithm for selecting a seam line automatically, which used to be selected by human operator for mosaicked images is presented. In addition to four factors proposed by automation theory, the FOM(Figure Of Merit) of tie point were taken into account to suggest the method to select a seam line applicatively and the algorithm was applied to mosaic test images.

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A Novel Graduation Algorithm in Image Mosaic

  • Luo, Wenfei;Li, Yan;Wang, Xiaoming
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1316-1318
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    • 2003
  • The Bernstein polynomial is one of the classic algorithms of panoramic images mosaic for shading into process applying in Virtual Reality modeling. Nevertheless, it is proven that the algorithm has its own limitation and weakness in applications. This paper was given the improved algorithm using Sinusoidal function for image mosaic. In order to put the new algorithm into image processing software as a flexible and general tool, it was further developed an extension for graduation image fusion and multi-images mosaic.

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A Study to Improve the Classification Accuracy of Mosaic Image over Korean Peninsula: Using PCA and RGB Indices (한반도 모자이크 영상의 분류 정확도 향상 기법 연구: PCA 기법과 RGB 지수를 활용하여)

  • Moon, Jiyoon;Lee, Kwangjae
    • Korean Journal of Remote Sensing
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    • v.38 no.6_4
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    • pp.1945-1953
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    • 2022
  • Korea Aerospace Research Institute produces mosaic images of the Korean Peninsula every year to promote the use of satellite images and provides them to users in the public sector. However, since the pan-sharpening and color balancing methodologies are applied during the mosaic image processing, the original spectral information is distorted. In addition, there is a limit to analyze using mosaic images as mosaic images provide only Red, Green and Blue bands excluding Near Infrared (NIR) band. Therefore, in order to compensate for these limitations, this study applied the Principal Component Analysis (PCA) technique and indices extracted from R, G, B bands together for image classification and compared the classification results. As a result of the analysis, the accuracy of the mosaic image classification result was about 67.51%, while the accuracy of the image classification result using both PCA and RGB indices was about 75.86%, confirming that the accuracy of the image classification result can be improved. As a result of comparing the PCA and the RGB indices, the accuracy of the image classification result was about 64.10% and 74.05% respectively. Through this, it was confirmed that the classification accuracy using the RGB indices was higher among the two techniques, and implications were derived that it was important to use high quality reference or supplementary data. In the future, additional indices and techniques are needed to improve the classification and analysis results of mosaic images, and related research is expected to increase the utilization of images that provide only R, G, B or limited spectral information.

Calculation of Objective Quality-Evaluation-Index for Mosaic Imagery (모자이크 영상의 객관적 품질평가지수 산정 방법)

  • Woo, Hee-Sook;Noh, Myoung-Jong;Park, June-Ku;Cho, Woo-Sug;Kim, Byung-Guk
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.3
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    • pp.33-40
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    • 2009
  • This paper proposes the assessment method for objective quality-evaluation-index of mosaic images. Quality assessment was evaluated using seam-line method and similarity and contrast of adjacent images. The evaluation measure was calculated based on selected evaluation criteria and compared with human visual inspection. It was found that quantitative quality evaluation measure showed that the evaluation results were similar to human visual check. Conclusively experimental results proved that proposed evaluation measure could be used for quantitative and objective quality assessment of mosaic images.

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REDUCING X-ray BRIGHT GALAXY GROUPS IMAGES WITH THELI PIPELINE

  • NIKAKHTAR, FARNIK
    • Publications of The Korean Astronomical Society
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    • v.30 no.2
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    • pp.671-673
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    • 2015
  • Before analyzing the images taken with a Mosaic CCD imager, the images have to reach a state which can be used for further scientific analysis. The transformation of raw images into calibrated images is called data reduction. Transforming HEavely Light into Images (THELI) is a nearly fully automated reduction pipeline software (Erben et al., 2005). This pipeline works on raw images to remove instrumental signatures, mask unwanted signals, and perform photometric and astrometric calibration. Finally THELI constructs a deep co-added mosaic image and a weight map. In this poster, THELI data reduction procedures will be reviewed and the reduction process for raw images of seven X-ray bright groups, extracted from GEMS groups (Osmond & Ponman, 2004) obtained by the Wide Field Imager (WFI) mounted on MPG/ESO telescope at La Silla in March 2006 will be discussed.

Mosaic Detection Based on Edge Projection in Digital Video (비디오 데이터에서 에지 프로젝션 기반의 모자이크 검출)

  • Jang, Seok-Woo;Huh, Moon-Haeng
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.5
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    • pp.339-345
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    • 2016
  • In general, mosaic blocks are used to hide some specified areas, such as human faces and disgusting objects, in an input image when images are uploaded on a web-site or blog. This paper proposes a new algorithm for robustly detecting grid mosaic areas in an image based on the edge projection. The proposed algorithm first extracts the Canny edges from an input image. The algorithm then detects the candidate mosaic blocks based on horizontal and vertical edge projection. Subsequently, the algorithm obtains real mosaic areas from the candidate areas by eliminating the non-mosaic candidate regions through geometric features, such as size and compactness. The experimental results showed that the suggested algorithm detects mosaic areas in images more accurately than other existing methods. The suggested mosaic detection approach is expected to be utilized usefully in a variety of multimedia-related real application areas.

Tunnel Mosaic Images Using Fisheye Lens Camera (어안렌즈 카메라를 이용한 터널 모자이크 영상 제작)

  • Kim, Gi-Hong;Song, Yeong-Sun;Kim, Baek-Seok
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.1
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    • pp.105-111
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    • 2009
  • A construction can be more convenient and safer with adequate informations. Consequently, studies on collecting various informations using newest surveying technology and applying these informations to a construction have been making progress recently. Digital images are easy to obtain and contain various informations. Therefore, with the recent development of image processing technology, the application field of digital images is getting wider. In this study, we proposed to use a fisheye lens camera in underground construction sites, especially tunnels, to overcome inconvenience in photographing with general lens cameras. A program for mapping the surface of a tunnel and making a mosaic image is also developed. This mosaic image can be applied to observe and analyze abnormal phenomenons on tunnel surface like cracks, water leakage, exfoliates, and so on.

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