High-Resolution Tolerance Against Noise Imaging Technique Based on Active Shift of Optical Axis
Shin Usuki* and Kenjiro T. Miura**
*Division of Global Research Leaders, Shizuoka University, Johoku 3-5-1, Naka-ku, Hamamatsu 432-8561, Japan
**Graduate School of Science and Technology, Shizuoka University, Johoku 3-5-1, Naka-ku, Hamamatsu 432-8561, Japan
Received:November 18, 2010Accepted:December 22, 2010Published:March 5, 2011
Keywords:pixel resolution, optical imaging, multiframe, image reconstruction, super-resolution
Optical imaging resolution is determined by both optical parameters such as light wavelength and the objective lens Numerical Aperture (NA) and by spatial sampling such as Charge-Coupled Device (CCD) camera pixel size. Focused on improving optical imaging pixel resolution, we reviewed multiframe Super-Resolution (SR) implemented in previous measurement to improve image resolution, but found its computational cost to high and calculation too long. Pixeldisplacement estimation also adversely affects resulting image quality and is difficult to apply practically due to SR registration calculation sensitivity to noise. The resolution improvement we have proposed uses active subpixel shifting of the optical axis based on actively controlling spatial image displacement using a glass-plate-parallel substrate and a galvano scanner. Multiframe SR registration is used but without pixel-displacement estimation. Theoretically, our proposal may improve image resolution stably at higher speed but to clarify this, we developed optics and rebuilt the multiframe SR.We then computationally analyzed improved resolution and noise tolerance using a Modulation Transfer Function (MTF). Optical and aliasing noise have been suppressed and image resolution improved in high measurement, making higherresolution imaging faster and cheaper thanks to our proposal.
Cite this article as:S. Usuki and K. Miura, “High-Resolution Tolerance Against Noise Imaging Technique Based on Active Shift of Optical Axis,” Int. J. Automation Technol., Vol.5 No.2, pp. 206-211, 2011.Data files:
-  S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Advances and Challenges in Super-Resolution,” Int. J. of Imaging Systems and Technology, Vol.14, Issue2, pp. 47-57, 2004.
-  S. Baker and T. Kanade, “Limits on Super-Resolution and How to Break Them,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.24, Issue9, pp. 1167-1183, 2002.
-  S. Aoki, “Super Resolution Processing by Plural Number of Lower Resolution Images,” Ricoh Technical Report, No.24, pp. 19-25, 1998.
-  W. J. Smith, “Modern Optical Engineering,” McGraw-Hill, 1966.
-  E. Kawamura, Y. Konno, and T. Yao, “Novel Optimization of Total Alighnment Error Factors,” Japanese J. of Applied Physics, Vol.36, Part 1, No.12B, pp. 7512-7516, 1997.