Identification of the blur extent from motion-blurred images

Yitzhak Yitzhaky; Norman S. Kopeika

doi:10.1117/12.210038

22 May 1995 Identification of the blur extent from motion-blurred images

Yitzhak Yitzhaky, Norman S. Kopeika

Proceedings Volume 2470, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VI; (1995) https://doi.org/10.1117/12.210038
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

In imaging systems in moving vehicles such as tanks, planes, ships, rpvs, etc., resolution is usually limited by motion blur. Successful restoration of blurred images depends primarily on the knowledge we have about the degradation process parameters, i.e., the point spread function (PSF) of the blur and the noise statistics. For many blur situations, such as those deriving from uniform or sinusoidal motion, the most important parameter for proper identification of the PSF is the blur extent parameter. This parameter is the smear size in the blurred image of a point object in the original image. A new method for identification of the blur extent in an image, blurred by motion of the camera during the exposure time, is presented in this paper. The blur extent identification is determined from the motion-blurred and noisy image itself. The identification method developed here is based on a concept that there exists a correlation between the pixels along the blur of the original unblurred pixels. In order to expose the hidden information about the blur extent, the blurred image is first transformed to a secondary image that is more informative about the blur extent, and then the blur extent is extracted from this image using correlation attributes in the image. This permits fast high resolution restoration when the blur extent can complete our knowledge about the blur properties.

Citation Download Citation

Yitzhak Yitzhaky and Norman S. Kopeika "Identification of the blur extent from motion-blurred images", Proc. SPIE 2470, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VI, (22 May 1995); https://doi.org/10.1117/12.210038

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