Image dehazing is a traditional task, yet it still presents arduous problems, especially in the removal of haze from texture and edge information an image. The state-of-the-art methods may result loss some visual informative details decrease quality. To improve quality, novel model proposed, based on fractional derivative data-driven regularization terms. In this model, contrast constrained ada...

In this paper, we present an extensive review on deep learning methods for image restoration tasks. Deep techniques, led by convolutional neural networks, have received a great deal of attention in almost all areas processing, especially classification. However, is fundamental and challenging topic plays significant roles understanding representation. It typically addresses deblurring, denoisin...

For photographs taken in outdoor environments, the air medium causes light attenuation, which reduces image quality; this effect is particularly obvious in hazy environments. To eliminate the hazy effect in images and improve the image quality, the present study proposes an efficient hybrid method. The proposed fuzzy estimator was adopted to estimate variations in light attenuation, and morphol...