Deep Image Compression Using Scene Text Quality Assessment
- URL: http://arxiv.org/abs/2305.11373v1
- Date: Fri, 19 May 2023 01:26:43 GMT
- Title: Deep Image Compression Using Scene Text Quality Assessment
- Authors: Shohei Uchigasaki, Tomo Miyazaki, Shinichiro Omachi
- Abstract summary: A high compression rate with general methods may degrade images, resulting in unreadable texts.
We develop a scene text image quality assessment model to assess text quality in compressed images.
- Score: 6.445605125467574
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- 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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