__Relative motion between the camera
and the pictured object occurs in various imaging situations, and causes an
image quality decrease. The phenomenon of motion blur is common when images are
taken using portable or moving systems such as digital cameras, robots,
satellites, mobile phones. Common motion types are: uniform velocity motion,
accelerated motion, and vibrations. Vibrations usually occur in systems that
include circular motion like in an engine, such as imaging systems placed on
airplanes or cars.
__In most researches that dealt with restoration of motion degraded images
using only the single blurred image, a uniform velocity motion was assumed or
an a priori parametric knowledge of the PSF was required.
__The method demonstrated here estimates the blur without an a priori
parametric knowledge of the PSF. In this method the identification of the blur
is done directly by filtering of the blurred image. The filtering is based on
the differences between the properties of images and general properties of the
motion blurs. The remaining filtered information characterizes the PSF. The
blur is assumed to be one-dimensional. This means that there are no significant
changes in the motion direction during the exposure.
__A future plan is an implementation of non-horizontal (chosen) motion
direction. Further plans are development for non- one-dimensional motion, and
implementation to real motion degraded image inserted by the user.
References
1. Y. Yitzhaky, I. Mor, A. Lantzman, and N. S. Kopeika,
"Direct method for restoration of motion-blurred images",
J. Opt. Soc. Am. A., 15(6), 1512-1519, June 1998.
2. Y. Yitzhaky, G. Boshusha, Y. Levi, and N. S. Kopeika,
"Vibrated image restoration from a single frame",
Optical Engineering, 38(8), August 2000.