Efficient Evaluation of Image Quality via Deep-Learning Approximation of Perceptual Metrics

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Artusi Alessandro; Banterle Francesco; Carrara Fabio; Moreo Alejandro;
  • Related identifiers: doi: 10.1109/TIP.2019.2944079
  • Subject: Convolutional Neural Networks (CNNs) | Objective Metrics | Image Evaluation | Human Visual System | JPEG-XT | HDR Imaging

mage metrics based on Human Visual System (HVS) play a remarkable role in the evaluation of complex image processing algorithms. However, mimicking the HVS is known to be complex and computationally expensive (both in terms of time and memory), and its usage is thus li... View more
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