SUR-Net : Predicting the Satisfied User Ratio Curve for Image Compression with Deep Learning

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2019
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Fan, Chunling
Zhang, Yun
Jiang, Qingshan
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IEEE COMPUTER SOCIETY, /, ed.. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX). Piscataway: IEEE, 2019, pp. 167-173. ISBN 978-1-5386-8212-8. Available under: doi: 10.1109/QoMEX.2019.8743204
Zusammenfassung

The Satisfied User Ratio (SUR) curve for a lossy image compression scheme, e.g., JPEG, characterizes the probability distribution of the Just Noticeable Difference (JND) level, the smallest distortion level that can be perceived by a subject. We propose the first deep learning approach to predict such SUR curves. Instead of the direct approach of regressing the SUR curve itself for a given reference image, our model is trained on pairs of images, original and compressed. Relying on a Siamese Convolutional Neural Network (CNN), feature pooling, a fully connected regression-head, and transfer learning, we achieved a good prediction performance. Experiments on the MCL-JCI dataset showed a mean Bhattacharyya distance between the predicted and the original JND distributions of only 0.072.

Zusammenfassung in einer weiteren Sprache
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004 Informatik
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Satisfied User Ratio, Just Noticeable Difference, Convolutional Neural Network, Deep Learning
Konferenz
2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX), 5. Juni 2019 - 7. Juni 2019, Berlin
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ISO 690FAN, Chunling, Hanhe LIN, Vlad HOSU, Yun ZHANG, Qingshan JIANG, Raouf HAMZAOUI, Dietmar SAUPE, 2019. SUR-Net : Predicting the Satisfied User Ratio Curve for Image Compression with Deep Learning. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX). Berlin, 5. Juni 2019 - 7. Juni 2019. In: IEEE COMPUTER SOCIETY, /, ed.. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX). Piscataway: IEEE, 2019, pp. 167-173. ISBN 978-1-5386-8212-8. Available under: doi: 10.1109/QoMEX.2019.8743204
BibTex
@inproceedings{Fan2019SURNe-49118,
  year={2019},
  doi={10.1109/QoMEX.2019.8743204},
  title={SUR-Net : Predicting the Satisfied User Ratio Curve for Image Compression with Deep Learning},
  isbn={978-1-5386-8212-8},
  publisher={IEEE},
  address={Piscataway},
  booktitle={2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)},
  pages={167--173},
  editor={IEEE Computer Society, /},
  author={Fan, Chunling and Lin, Hanhe and Hosu, Vlad and Zhang, Yun and Jiang, Qingshan and Hamzaoui, Raouf and Saupe, Dietmar}
}
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