Deep blind image quality assessment by learning sensitivity map

Jongyoo Kim, Woojae Kim, Sanghoon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Applying a deep convolutional neural network CNN to no-reference image quality assessment (NR-IQA) is a challenging task due to the lack of a training database. In this paper, we propose a CNN-based NR-IQA framework that can effectively solve this problem. The proposed method-the Deep Blind image Quality Assessment predictor (DeepBQA)-adopts two step training stages to avoid overfitting. In the first stage, a ground-truth objective error map is generated and used as a proxy training target. Then, in the second stage, subjective score is predicted by learning a sensitivity map, which weights each pixel in the predicted objective error map. To compensate the inaccurate prediction of the objective error on the homogeneous regions, we additionally suggest a reliability map. Experiments showed that DeepBQA yields a state-of-the-art correlation with human opinions.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6727-6731
Number of pages5
ISBN (Print)9781538646588
DOIs
Publication statusPublished - 2018 Sep 10
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 2018 Apr 152018 Apr 20

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Conference

Conference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period18/4/1518/4/20

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Kim, J., Kim, W., & Lee, S. (2018). Deep blind image quality assessment by learning sensitivity map. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (pp. 6727-6731). [8462369] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2018.8462369