• Title/Summary/Keyword: Poisson image editing

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Stereo Image Composition Using Poisson Object Editing (포아송 객체 편집을 이용한 스테레오 영상 합성)

  • Baek, Eu-Tteum;Ho, Yo-Sung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.8
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    • pp.453-458
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    • 2014
  • In this paper, we propose a stereo image composition method based on Poisson image editing. If we synthesize images without considering their depth values, it may lead to unwanted consequences. When we segment an image into its background and foreground regions using Grabcut, we take into account their geometric positions to mix color tones; thus, the image is composited more naturally. After synthesizing images, we apply a blurring operation around object boundaries; then, the foreground object and background are composited more seamlessly. In addition, we can adjust the distance of the object by setting arbitrary depth values and generating right color and depth images automatically. Experimental results show that the proposed stereo image composition method provides naturally synthesized stereo images. Improved portions were subjectively confirmed as well.

Composition of Foreground and Background Images using Optical Flow and Weighted Border Blending (옵티컬 플로우와 가중치 경계 블렌딩을 이용한 전경 및 배경 이미지의 합성)

  • Gebreyohannes, Dawit;Choi, Jung-Ju
    • Journal of the Korea Computer Graphics Society
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    • v.20 no.3
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    • pp.1-8
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    • 2014
  • We propose a method to compose a foreground object into a background image, where the foreground object is a part (or a region) of an image taken by a front-facing camera and the background image is a whole image taken by a back-facing camera in a smart phone at the same time. Recent high-end cell-phones have two cameras and provide users with preview video before taking photos. We extract the foreground object that is moving along with the front-facing camera using the optical flow during the preview. We compose the extracted foreground object into a background image using a simple image composition technique. For better-looking result in the composed image, we apply a border smoothing technique using a weighted-border mask to blend transparency from background to foreground. Since constructing and grouping pixel-level dense optical flow are quite slow even in high-end cell-phones, we compute a mask to extract the foreground object in low-resolution image, which reduces the computational cost greatly. Experimental result shows the effectiveness of our extraction and composition techniques, with much less computational time in extracting the foreground object and better composition quality compared with Poisson image editing technique which is widely used in image composition. The proposed method can improve limitedly the color bleeding artifacts observed in Poisson image editing using weighted-border blending.