English

Image Distortion Detection using Convolutional Neural Network

Computer Vision and Pattern Recognition 2018-05-29 v1

Abstract

Image distortion classification and detection is an important task in many applications. For example when compressing images, if we know the exact location of the distortion, then it is possible to re-compress images by adjusting the local compression level dynamically. In this paper, we address the problem of detecting the distortion region and classifying the distortion type of a given image. We show that our model significantly outperforms the state-of-the-art distortion classifier, and report accurate detection results for the first time. We expect that such results prove the usefulness of our approach in many potential applications such as image compression or distortion restoration.

Keywords

Cite

@article{arxiv.1805.10881,
  title  = {Image Distortion Detection using Convolutional Neural Network},
  author = {Namhyuk Ahn and Byungkon Kang and Kyung-Ah Sohn},
  journal= {arXiv preprint arXiv:1805.10881},
  year   = {2018}
}

Comments

Accepted to ACPR 2017

R2 v1 2026-06-23T02:10:22.660Z