Advances and Applications in Discrete Mathematics
Volume 20, Issue 2, Pages 295 - 304
(March 2019) http://dx.doi.org/10.17654/ |
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HAZE REMOVAL USING IMPROVED AUTOMATIC QUICK SHIFT SEGMENTATION
Humera Tariq, Asia Samreen and Usman Amjad
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Abstract: Bad weather (such as fog, haze, mist) brings trouble to many computer vision applications like outdoor surveillance systems, object detection, pedestrian detection and intelligent transport systems. Dark channel method with fixed rectangular patches is used in many algorithms for the removal of fog. The paper aims at an improved dark channel prior where fixed rectangular patches are replaced by homogeneous regions, called superpixels. In most cases, superpixels are obtained when quick shift segmentation with fixed parameters has been employed. The proposed quick shift is automatic in nature and determines optimal parameters on the fly to obtain dark channel image. To judge improvement in visibility, a reference k-means based image is used. Improved algorithm based on k-means and quick shift segmentation has been proposed which is qualitatively more effective than other state of art methods in terms of edge visibility, halo effects and restoration of natural scene radiance. |
Keywords and phrases: automatic quick shift, dark channel, fog removal, superpixel, segmentation.
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