• Title/Summary/Keyword: RGB Color

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A Study on the Feature Extraction Using Spectral Indices from WorldView-2 Satellite Image (WorldView-2 위성영상의 분광지수를 이용한 개체 추출 연구)

  • Hyejin, Kim;Yongil, Kim;Byungkil, Lee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.5
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    • pp.363-371
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    • 2015
  • Feature extraction is one of the main goals in many remote sensing analyses. After high-resolution imagery became more available, it became possible to extract more detailed and specific features. Thus, considerable image segmentation algorithms have been developed, because traditional pixel-based analysis proved insufficient for high-resolution imagery due to its inability to handle the internal variability of complex scenes. However, the individual segmentation method, which simply uses color layers, is limited in its ability to extract various target features with different spectral and shape characteristics. Spectral indices can be used to support effective feature extraction by helping to identify abundant surface materials. This study aims to evaluate a feature extraction method based on a segmentation technique with spectral indices. We tested the extraction of diverse target features-such as buildings, vegetation, water, and shadows from eight band WorldView-2 satellite image using decision tree classification and used the result to draw the appropriate spectral indices for each specific feature extraction. From the results, We identified that spectral band ratios can be applied to distinguish feature classes simply and effectively.

Digital Hologram Compression Technique using Multi-View Prediction based on Image Accumulation (영상집적 기반의 다시점 부호화 기술을 이용한 디지털 홀로그램의 압축 기술)

  • Choi, Hyun-Jun;Seo, Young-Ho;Bae, Jin-Woo;Yoo, Ji-Sang;Kim, Hwa-Sung;Kim, Dong-Wook
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.10C
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    • pp.933-941
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    • 2006
  • In this paper, we proposed an efficient coding method for digital hologram (fringe pattern) acquired by a CCD camera or by computer generation using multi-view prediction technique and MPEG video compression standard technique. It proceeds each R, G, or B color component separately. The basic processing unit is a partial image segmented into the size of $N{\times}N$. Each partial image retains the information of the whole object. This method generates an assembled image for a row of the segmented and frequency-transformed partial images, which is the basis of the coding process. That is, a motion estimation and compensation technique of MPEG is applif:d to the reconstructed images from the assembled images with the disparities found during generation of assembled image and the original partial images. Therefore the compressed results are the disparity of eachpartial image to form the assembled image for the corresponding row, assembled image, and the motion vectors and the compensated image for each partial image. The experimental results with the implemented algorithm showed that the proposed method has NC (Normal Correlation) values about 4% higher than the previous method, by which ours has better compression efficiency. Consequently, the Proposed method is expected to be used effectively in the application areas to transmit the digital hologram data. can be identified in comparison with the previous researches and commercial IPs.

Generation of Feature Map for Improving Localization of Mobile Robot based on Stereo Camera (스테레오 카메라 기반 모바일 로봇의 위치 추정 향상을 위한 특징맵 생성)

  • Kim, Eun-Kyeong;Kim, Sung-Shin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.1
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    • pp.58-63
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    • 2020
  • This paper proposes the method for improving the localization accuracy of the mobile robot based on the stereo camera. To restore the position information from stereo images obtained by the stereo camera, the corresponding point which corresponds to one pixel on the left image should be found on the right image. For this, there is the general method to search for corresponding point by calculating the similarity of pixel with pixels on the epipolar line. However, there are some disadvantages because all pixels on the epipolar line should be calculated and the similarity is calculated by only pixel value like RGB color space. To make up for this weak point, this paper implements the method to search for the corresponding point simply by calculating the gap of x-coordinate when the feature points, which are extracted by feature extraction and matched by feature matching method, are a pair and located on the same y-coordinate on the left/right image. In addition, the proposed method tries to preserve the number of feature points as much as possible by finding the corresponding points through the conventional algorithm in case of unmatched features. Because the number of the feature points has effect on the accuracy of the localization. The position of the mobile robot is compensated based on 3-D coordinates of the features which are restored by the feature points and corresponding points. As experimental results, by the proposed method, the number of the feature points are increased for compensating the position and the position of the mobile robot can be compensated more than only feature extraction.

A Study to Improve the Accuracy of Segmentation and Classification of Mosaic Images over the Korean Peninsula (한반도 모자이크 영상의 분할 및 분류 정확도 향상을 위한 연구)

  • Moon, Jiyoon;Lee, Kwang Jae
    • Korean Journal of Remote Sensing
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    • v.37 no.6_3
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    • pp.1943-1949
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    • 2021
  • In recent years, as the demand of high-resolution satellite images increases due to the miniaturization and constellation of satellites, various efforts to support users to utilize satellite images more conveniently are performed. Accordingly, the Korea Aerospace Research Institute produces and provides mosaic images on the Korean Peninsula every year to improve the convenience of users in the public sector and activate the use of satellite images. In order to increase the utilization of mosaic images on the Korean Peninsula, a study on satellite image segmentation and classification using mosaic images was attempted. However, since mosaic images provide only R, G, and B bands and processes such as image sharpening and color balancing are applied, there is a limitation that the spectral information of original images is distorted, so various indices were extracted and classified using R, G, and B bands to compensate for this. As a result of the study, the accuracy of image classification results using only mosaic images was about 72%, while the accuracy of image classification results using indices extracted from R, G, and B bands together was about 79%. Through this, it was confirmed that when performing image classification using mosaic images on the Korean Peninsula, the image classification results can be improved if the indices extracted from R, G, and B bands are used together. These research results are expected to be applied not only to mosaic images but also to images in which spectral information is limited or only R, G, and B bands are provided.