Haze hampers the performance of vision systems. So, removal of haze appearance\nin a scene should be the first-priority for clear vision. It finds wide\nspectrum of practical applications. A good number of dehazing techniques\nhave already been developed. However, validation with the help of ground\ntruth i.e. simulated haze on a clear image is an ultimate necessity. To address\nthis issue, in this work synthetic haze images with various haze concentrations\nare simulated and then used to confirm the validation task of dark-channel\ndehazing mechanism, as it is a very promising single image dehazing technique.\nThe simulated hazy image is developed using atmospheric model with\nand without Perlin noise. The effectiveness of dark-channel dehazing method\nis confirmed using the simulated haze images through average gradient metric,\nas haze reduces the gradient score.
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