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.

翻译：图像压缩是互联网通信工程中的一项基础技术。然而，采用通用方法进行高压缩率压缩可能导致图像质量下降，致使文本难以辨认。本文提出了一种旨在保持文本质量的图像压缩方法。我们开发了一个场景文本图像质量评估模型，用于评估压缩图像中的文本质量。该评估模型通过迭代搜索方式寻找具有高质量文本的最佳压缩图像。客观与主观评估结果表明，所提方法优于现有方法。此外，所提出的评估模型在性能上超越了其他深度学习回归模型。