IJE TRANSACTIONS B: Applications Vol. 32, No. 2 (February 2019) 249-255    Article in Press

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F. Azari Nasrabad, H. Hassanpour and S. Asadi Amiri
( Received: October 27, 2018 – Accepted in Revised Form: January 03, 2019 )

Abstract    The dark channel prior (DCP) technique is an effective method to enhance hazy images. Dark channel is an image with the same size as the hazy image which represents the haze severity in different places of the image. The DCP method suffers from two problems: it is incapable for removing haze from smooth regions, causing blocking effects on these areas; it cannot properly reduce a haze with a non-monotonic behavior. In this paper, an adaptive image dehazing method is proposed based on the DCP method to solve the problem of this method. In this method, to overcome the dark channel deficiency of the blocking effects, the dark channel is initially extracted. The hazy image is subsequently segmented into smooth and non-smooth regions. Regarding the smooth regions, the pixel values in the dark channel are reduced by dividing them with a rather great number. To solve the second problem, depending upon the haze severity, the haze removing technique is applied repeatedly until all the regions of the image are enhanced. Finally, the Gamma correction approach is used for contrast enhancement of the smooth regions. The performed subjective and objective comparison attest the superiority of the proposed method to the DCP one in removing the haze.


Keywords    Dehazing, Image enhancement, Dark channel prior, Segmentation.



روش کانال تاریک یک روش موثر برای بالا بردن کیفیت تصاویر دارای مه است. کانال تاریک، تصویری هم اندازه با تصویر مه آلود است که میزان مه را در قسمت‌‌¬های مختلف تصویر نشان می¬دهد. روش کانال تاریک دارای دو مشکل است: قادر به حذف مه از نواحی هموار نیست و موجب ایجاد اثر بلوکی در این نواحی می¬¬شود. همچنین این روش برای تصاویر دارای مه ناهمگن مناسب نیست. در این مقاله یک روش حذف مه بر اساس روش کانال تاریک پیشنهاد شده است. در این روش برای غلبه بر مشکل اثر بلوکی در نواحی هموار، ابتدا تصویر کانال تاریک استخراج می¬شود. سپس این تصویر به قسمت¬های هموار و غیر هموار تقسیم می-شود. با توجه به نواحی هموار، مقادیر پیکسل¬های متناظر در کانال تاریک با تقسیم بر یک عدد بزرگ کاهش می¬یابد. برای حل مشکل دوم با توجه به میزان مه، ممکن است این روش بارها تکرار شود تا کل تصویر بهبود یابد. در نهایت اصلاح گاما برای بالا بردن کیفیت نواحی هموار به کار می¬رود. مقایسه کمی و کیفی، برتری روش پیشنهادی بر روش کانال تاریک را نشان می¬دهد.


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