Image sharpening using image sequence and independent component analysis

Ivica Kopriva; Qian Du; Harold H. Szu

doi:10.1117/12.542122

12 April 2004 Image sharpening using image sequence and independent component analysis

Ivica Kopriva, Qian Du, Harold H. Szu

Proceedings Volume 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II; (2004) https://doi.org/10.1117/12.542122
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

Ivica Kopriva, Qian Du, and Harold H. Szu "Image sharpening using image sequence and independent component analysis", Proc. SPIE 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II, (12 April 2004); https://doi.org/10.1117/12.542122

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