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Full Version: Numericals for total variation-based reconstruction of motion blurred images
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Numericals for total variation-based reconstruction of
motion blurred images



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Introduction

Motion blur occurs in many image formation systems due to low light conditions or fast
motion of an object. If a camera has slow shutter speed relative to the object velocity, the
obtained image is degraded by motion blur. When a photograph is taken in low light conditions
or of a fast moving object, motion blur can cause significant degradation of the image. Both the
moving object and camera shake contribute to this blurring. Blurred images can be restored
when the blur function is known [2]. In this paper uniform motion blur is described. The model
used is z = Ku + n, in which z is the observed image, u is the real image, K is a known linear
blur operator and n is a noise.



Numerical experiments


In the numerical experiments, we focus on the image motion deblurring problem computed
by schemes (3.1) to (3.5). The original image denoted by ue has 256×256 pixels. The operators
of horizontal blur, vertical blur and angled blur are performed on the original image ue.