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Proceedings Paper

Restoration of non-uniform exposure motion blurred image
Author(s): Yuanhong Luo; Tingfa Xu; Ningming Wang; Feng Liu
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Paper Abstract

Restoring motion-blurred image is the key technologies in the opto-electronic detection system. The imaging sensors such as CCD and infrared imaging sensor, which are mounted on the motion platforms, quickly move together with the platforms of high speed. As a result, the images become blur. The image degradation will cause great trouble for the succeeding jobs such as objects detection, target recognition and tracking. So the motion-blurred images must be restoration before detecting motion targets in the subsequent images. On the demand of the real weapon task, in order to deal with targets in the complex background, this dissertation uses the new theories in the field of image processing and computer vision to research the new technology of motion deblurring and motion detection. The principle content is as follows: 1) When the prior knowledge about degradation function is unknown, the uniform motion blurred images are restored. At first, the blur parameters, including the motion blur extent and direction of PSF(point spread function), are estimated individually in domain of logarithmic frequency. The direction of PSF is calculated by extracting the central light line of the spectrum, and the extent is computed by minimizing the correction between the fourier spectrum of the blurred image and a detecting function. Moreover, in order to remove the strip in the deblurred image, windows technique is employed in the algorithm, which makes the deblurred image clear. 2) According to the principle of infrared image non-uniform exposure, a new restoration model for infrared blurred images is developed. The fitting of infrared image non-uniform exposure curve is performed by experiment data. The blurred images are restored by the fitting curve.

Paper Details

Date Published: 24 November 2014
PDF: 9 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93013M (24 November 2014); doi: 10.1117/12.2082837
Show Author Affiliations
Yuanhong Luo, Science and Technology on Optical Radiation Lab. (China)
Beijing Institute of Technology (China)
Tingfa Xu, Beijing Institute of Technology (China)
Ningming Wang, Science and Technology on Optical Radiation Lab. (China)
Feng Liu, Science and Technology on Optical Radiation Lab. (China)


Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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