Study of the Dynamic Image Stabilizer

Article Preview

Abstract:

Most anti-shake technologies can compensate the hand shake when taking a static picture. When people use the camera in the dim environment, the shutter opening time will be extended to increase exposure. However, the hand shake will cause the photos blurry if the shutter opening time was too long. The hand shake problem is even more serious when people doing the dynamic image recording. In the past years, the mobile phones with the digital camera and portable video camera were developed vigorously. Taking pictures and recording dynamic image have become the basic functions of mobile phones since the development of the 3G mobile phone. While the specifications of cameras become high resolution and high magnification optical zoom, the traditional electronic anti-shake technology will not be applied in the digital camera because of the large amount of computing power. It is also difficult to apply the optical anti-shake technology in thin 3C products because the volume of optical anti-shake module is too large. Thus, developing a new anti-shake technology which can be applied in the thin 3C products to enhance the photo and video quality is very important. In this paper, the image processing technologies will be applied to calculate the motion signal. Then, the voluntary and involuntary motion signals will be separated by the signal separation algorithm, and finally the dynamic image will be reconstruction by compensating the involuntary shake of each frame to enhance the quality of the dynamic image.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1275-1278

Citation:

Online since:

May 2015

Keywords:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] S. Battiato, A. Castorina, M. Guarnera, and P. Vivirito, Yo: IEEE Transactionson Consumer Electronics Vol. 49 (2003), pp.670-675.

DOI: 10.1109/tce.2003.1233798

Google Scholar

[2] A. Bosco, K. Findlater, S. Battiato, and A. Castorina: IEEE Transactions on Consumer Electronics Vol. 49 (2003), pp.676-682.

DOI: 10.1109/tce.2003.1233800

Google Scholar

[3] K. Uomori, A. Morimura, H. Ishii, T. Sakaguchi, and Y. Kitamura: IEEE Trans. Consum. Electron. Vol. 36 (1990), p.510–519.

DOI: 10.1109/30.103167

Google Scholar

[4] F. Vella, A. Castorina, M. Mancuso, and G. Messina: IEEE Trans. Consum. Electron. Vol. 48 (2002), p.796–800.

Google Scholar

[5] Z. Pan and C. W. Ngo: IEEE Trans. Consum. Electron. Vol. 51 (2005), p.1074–1084.

Google Scholar

[6] S. Erturk: IEEE Trans. Consum. Electron. Vol. 49 (2003), p.1320–1325.

Google Scholar

[7] S. Erturk: Proc. 2nd Int. Symp. Image Signal Process. Anal. (2001), p.266–271.

Google Scholar

[8] S. Erturk: Real-Time Imaging Vol. 8 (2002), p.317–328.

Google Scholar

[9] Y. Matsushita, E. Ofek, G. Weina, X. Tang, and H. -Y. Shum: IEEE Trans. Pattern Anal. Machine Intell. Vol. 28 (2006), p.1150–1163.

DOI: 10.1109/tpami.2006.141

Google Scholar

[10] H. C. Chang, S. H. Lai, and K. R. Lu: J. Vis. Commun. Image Represent. Vol. 17 (2006), p.659–673.

Google Scholar

[11] Y. M. Liang, H. R. Tyan, S. L. Chang, H. Y. M. Liao, and S. W. Chen: IEEE Trans. Veh. Technol. Vol. 53 (2004), p.1636–1648.

Google Scholar