Adaptive Image Restoration for Video Surveillance: A Real-Time Approach
Journal:
arXiv
Published Date:
May 19, 2025
Abstract
One of the major challenges in the field of computer vision especially for
detection, segmentation, recognition, monitoring, and automated solutions, is
the quality of images. Image degradation, often caused by factors such as rain,
fog, lighting, etc., has a negative impact on automated
decision-making.Furthermore, several image restoration solutions exist,
including restoration models for single degradation and restoration models for
multiple degradations. However, these solutions are not suitable for real-time
processing. In this study, the aim was to develop a real-time image restoration
solution for video surveillance. To achieve this, using transfer learning with
ResNet_50, we developed a model for automatically identifying the types of
degradation present in an image to reference the necessary treatment(s) for
image restoration. Our solution has the advantage of being flexible and
scalable.
