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Refining the Transmission Map and Air Light in the Atmospheric Light Scattering Model for An Efficient Single Image Dehazing Method
  • Yucel ÇİMTAY
Yucel ÇİMTAY
TED University

Corresponding Author:[email protected]

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Abstract

Many dehazing methods have been presented by many researchers either on single hazy images or multiple images like videos. With the increasing volume of hazy image datasets, recent literature about dehazing is mostly based on deep learning methods. Although, deep learning models perform better than traditional methods on the validation data of the specific dataset which they are trained with, the generalization performance of deep learning models is generally poor. Another important bottleneck for deep models is the training cost in terms of time and hardware requirements. In this study, traditional DCP method is improved by taking into account the amount of haze and refining the transmission and air light used in atmospheric light scattering model of haze. Results of this study shows that proposed method is superior and/or competitive to traditional DCP method and state of the art deep learning models in terms of the visual quality of the dehazed image.