• Title/Summary/Keyword: 고속다중노출영상

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The Measurement of Flight Data of Golfball with High-Speed Multi-Exposure Image (고속 다중 노출 영상을 이용한 골프공의 비행 요소 측정)

  • Kim, Ki-Hyun;Park, Hyun-Woo;Ju, Woo-Suk;Lee, Dong-Hoon;Yun, Tae-Soo
    • Journal of Korea Multimedia Society
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    • v.12 no.5
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    • pp.699-707
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    • 2009
  • Recently, while 3D sports game increases, the research that it recognizes the operation of the real user actively progresses. Most of all, the research about the golf is active. In this paper, the camera acquiring in a high-speed multi-exposure image measures the flight data of the golf ball through the image processing. While photographing, the high-speed camera, using this system, exposes an image at regular intervals. And line scan camera checks whether the golf ball passed or not. After the location information of the calculated golf ball calculates a speed and a direction by using the physical formula, it applies the golf simulation. After, this system is possible the measurement of the physical element of the spherical object.

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Fast Multiple-Image-Based Deblurring Method (다중 영상 기반의 고속 처리용 디블러링 기법)

  • Son, Chang-Hwan;Park, Hyung-Min
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.4
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    • pp.49-57
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    • 2012
  • This paper presents a fast multiple-image-based deblurring method that decreases the computation loads in the image deblurring, enhancing the sharpness of the textures or edges of the restored images. First, two blurred images with some blurring artifacts and one noisy image including severe noises are consecutively captured under a relatively long and short exposures, respectively. To improve the processing speeds, the captured multiple images are downsampled at the ratio of two, and then a way of estimating the point spread function(PSF) based on the image or edge patches extracted from the whole images, is introduced. The method enables to effectively reduce the computation time taken in the PSF prediction. Next, the texture-enhanced image deblurring method of supplementing the ability of the texture representation degraded by the downsampling of the input images, is developed and then applied. Finally, to get the same image size as the original input images, an upsampling method of utilizing the sharp edges of the captured noisy image is applied. By using the proposed method, the processing times taken in the image deblurring, which is the main obstacle of its application to the digital cameras, can be shortened, while recovering the fine details of the textures or edge components.