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Proceedings Paper

Restoration of motion blurred image with Lucy-Richardson algorithm
Author(s): Jing Li; Zhao Hui Liu; Liang Zhou
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Paper Abstract

Images will be blurred by relative motion between the camera and the object of interest. In this paper, we analyzed the process of motion-blurred image, and demonstrated a restoration method based on Lucy-Richardson algorithm. The blur extent and angle can be estimated by Radon transform algorithm and auto-correlation function, respectively, and then the point spread function (PSF) of the motion-blurred image can be obtained. Thus with the help of the obtained PSF, the Lucy-Richardson restoration algorithm is used for experimental analysis on the motion-blurred images that have different blur extents, spatial resolutions and signal-to-noise ratios (SNR’s). Further, its effectiveness is also evaluated by structural similarity (SSIM). Further studies show that, at first, for the image with a spatial frequency of 0.2 per pixel, the modulation transfer function (MTF) of the restored images can maintains above 0.7 when the blur extent is no bigger than 13 pixels. That means the method compensates low frequency information of the image, while attenuates high frequency information. At second, we fund that the method is more effective on condition that the product of the blur extent and spatial frequency is smaller than 3.75. Finally, the Lucy-Richardson algorithm is found insensitive to the Gaussian noise (of which the variance is not bigger than 0.1) by calculating the MTF of the restored image.

Paper Details

Date Published: 8 October 2015
PDF: 6 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 967519 (8 October 2015); doi: 10.1117/12.2199337
Show Author Affiliations
Jing Li, Xi'an Institute of Optics and Precision Mechanics (China)
Zhao Hui Liu, Xi'an Institute of Optics and Precision Mechanics (China)
Liang Zhou, Xi'an Institute of Optics and Precision Mechanics (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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