Image sharpening using image sequence and independent component analysis

被引:1
作者
Kopriva, I [1 ]
Du, Q [1 ]
Szu, H [1 ]
机构
[1] George Washington Univ, Dept Elect & Comp Engn, Digital Media RF Lab, Washington, DC 20052 USA
来源
INDEPENDENT COMPONENT ANALYSES, WAVELETS, UNSUPERVISED SMART SENSORS, AND NEURAL NETWORKS II | 2004年 / 5439卷
关键词
image sharpening; image sequence; independent component analysis;
D O I
10.1117/12.542122
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The novel approach to the image sharpening problem is proposed in this paper. It is based on the application of the independent component analysis (ICA) algorithm on the image sequence with the appropriate time displacement between the image frames. The novelty is in the data representation required by the ICA algorithms where each selected image frame has been used as a sensor implying that underlying sources are temporally independent. The proposed concept enables blurring effects contributed by atmospheric turbulence to be extracted as separate physical sources. It has been ensured through images registration technique that motion of the video recorder is compensated. Encouraging preliminary results were obtained when ICA algorithm has been applied on the experimental data (video sequence) with the known ground truth. It has been verified that extracted spatial turbulence patterns are highly impulsive with Gaussian exponent between 0.5 and 0.6 where Laplacian distribution is characterized with Gaussian exponent 1.
引用
收藏
页码:63 / 73
页数:11
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