Synthetic Aperture Imaging Beyond Foreground Using Image Matting

被引:0
|
作者
Yihua Pan
Bin Liu
Wenmin Yan
Yan Han
Yi Zhang
机构
[1] North University of China,School of Information and Communication Engineering
[2] North University of China,Shanxi Key Laboratory of Information Detection and Processing
[3] Science and Technology on Transient Impact Laboratory,undefined
来源
Sensing and Imaging | 2019年 / 20卷
关键词
Computational imaging; Synthetic aperture imaging; Labeling; Image matting; Occlusion removing;
D O I
暂无
中图分类号
学科分类号
摘要
Synthetic aperture imaging is widely applied to reconstruct the occluded objects. Unfortunately, due to the superimposition of foreground rays, blurriness occurs in reconstructed images, which leads to an undesirable quality of reconstruction result. Screening effective rays before synthetic aperture imaging become the key to improve the quality of reconstructed image. In this paper, we propose a method to remove interference from occlusion in synthetic aperture imaging by using image matting. By focusing on the occlusion plane, the focusing degree of synthetic aperture imaging result can roughly label occlusions and non-occlusions. These labels can serve as the scribbles of input image of image matting, which can distinguish occlusions and backgrounds more precisely. After that, the focusing at the desired depth is by averaging pixels without occlusions. The experimental results show that our method can effectively remove the blur in the reconstruction results. We demonstrate the superiority of our method by presenting experimental results as well as comparing our method with other’s methods.
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