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arXiv · 2305.11373

Deep Image Compression Using Scene Text Quality Assessment

Shohei Uchigasaki·Tomo Miyazaki·Shinichiro Omachi
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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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Shohei Uchigasaki, Tomo Miyazaki, Shinichiro Omachi. 2023-05-19. Deep Image Compression Using Scene Text Quality Assessment. https://doi.org/10.1016/j.patcog.2023.109696

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