Deep Image Compression Using Scene Text Quality Assessment

Shohei Uchigasaki, Tomo Miyazaki, Shinichiro Omachi
5/19/2023
cs.CV

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Abstract

Image compression is a fundamental technology for Internet communication engineering. However, a high compression rate with general methods may degrade images, resulting in unreadable texts. In this paper, we propose an image compression method for maintaining text quality. We developed a scene text image quality assessment model to assess text quality in compressed images. The assessment model iteratively searches for the best-compressed image holding high-quality text. Objective and subjective results showed that the proposed method was superior to existing methods. Furthermore, the proposed assessment model outperformed other deep-learning regression models.

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Cite this paper

@article{uchigasaki2023deep,
  title  = {Deep Image Compression Using Scene Text Quality Assessment},
  author = {Shohei Uchigasaki and Tomo Miyazaki and Shinichiro Omachi},
  year   = {2023},
  eprint = {2305.11373},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.11373v1}
}

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