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Background
Overview

            Image processing the global area
that involve 1) enhance and improving the visual appearance of images for human
scenes 2) preparing images for measurement measuring features and current
structures. When atmospheric moisture effect on the scenes it will safely
degrades the visibility of outdoor scenes it is called haze1. Haze fetches trouble to many computer vision and affect
frequently on graphics applications as it minify the clarity of the scene2. So attenuation (decreases the disparity) and the air light (increases
the whiteness) are the two fundamental phenomena those cause a haze, figure 1 illustrate both attenuation and air light
phenomena.

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Figure
1 Attenuation and air light phenomena

The
collaborations between atmosphere and the light causes fog and haze like
absorption, dispersion, and emission, but basically they are different in the
sizes and types of scattering particles3.

In
recent year there are many techniques used in many computer vision applications
that recover the color and contrast of the scene to remove this haze, such as
outdoor surveillance, object detection, consumer electronics, enhancement etc.1.

Usually when remove the haze, which is called
dehazing, is commonly performed under the physical degradation model, which
presuppose a solution of problem is not reversed4.

Most
picture dehazing algorithms consider utilizing a hard brim presumptions or
customer contribution to evaluate atmospheric light5. According to (C. Chengtao1,) 6 they are characterized the various dehazing picture approaches
into two general classifications i.e. picture improvement and regain physical
model. Image-dehazing methods can be roughly categorized into two kinds: the
methods based on computer visions and those based on physical models. The
advantage of computer-visionbased methods is that they can do the dehazing
process by utilizing only one single image7.

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