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Automated Removal of Partial Occlusion Blur

  • Scott McCloskey
  • Michael Langer
  • Kaleem Siddiqi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4843)

Abstract

This paper presents a novel, automated method to remove partial occlusion from a single image. In particular, we are concerned with occlusions resulting from objects that fall on or near the lens during exposure. For each such foreground object, we segment the completely occluded region using a geometric flow. We then look outward from the region of complete occlusion at the segmentation boundary to estimate the width of the partially occluded region. Once the area of complete occlusion and width of the partially occluded region are known, the contribution of the foreground object can be removed. We present experimental results which demonstrate the ability of this method to remove partial occlusion with minimal user interaction. The result is an image with improved visibility in partially occluded regions, which may convey important information or simply improve the image’s aesthetics.

Keywords

Complete Occlusion Foreground Object Partial Occlusion Occlude Object Background Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Scott McCloskey
    • 1
  • Michael Langer
    • 1
  • Kaleem Siddiqi
    • 1
  1. 1.Centre for Intelligent Machines, McGill University 

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