Semantic Aware Just Noticeable Differences for VVC compressed Text Screen Content Images

Kaifang Yang, Xinrong Zhao, Yanchao Gong

Abstract: With the rapid development of multimedia applications such as online education, remote conferences, and telemedicine, an emerging type of image known as text screen content images (TSCI) has gained widespread utilization. Distinguishing from natural images captured by cameras, TSCI is generally generated or rendered by computers and exhibits significant differences in content characteristics. Notably, TSCI primarily comprises text,, a symbol system uniquely defined by humans with specific semantics. As an important carrier for transmitting semantic information, the quality of text in TSCI significantly affects the subjective perception experience of multimedia system users. Just noticeable difference (JND) is a widely studied image quality measure that is theoretically closest to human perception. However, the traditional JND (T-JND) tests fail to distinguish text from other image contents, ignoring the significant impact of semantic readability of text on image quality. This paper focuses for the first time on the impact of text semantics on the quality of TSCI, and JND experiments for TSCI compressed by the state-of-the-art versatile video coding (VVC) standard are explored and discussed. Specifically, a matching TSCI database is first established. Using the database, image subjective observation comparison experiments are further designed and carried out to construct the traditional JND (T-JND) as well as the semantic aware JND (S-JND). By comparing the experimental results, crucial conclusions are reached, including the fact that the S-JND provides a more precise description of the quality of TSCI compared to the T-JND. These conclusions have important guiding significance for the subsequent development of efficient JND models suitable for TSCI compressed by VVC.

Primary Subject Area: [Experience] Interactions and Quality of Experience

Relevance To Conference: Image quality assessment is one of the key technologies to ensure the effective operation of multimedia communication systems. Just noticeable difference (JND), which is characterized by the minimum detectable amount of two visual stimuli, has been widely studied in image quality assessment. However, traditional JND (T-JND) tests cannot be effectively applied to text screen content images (TSCI) as they ignore the influence of text semantics. Therefore, to ensure the operational efficiency of multimedia systems that contain a large amount of TSCIs, such as online education, remote conferences, and telemedicine, the development of a suitable JND test considering text semantic information becomes an urgent research topic. This paper provides a novel semantic aware JND (S-JND) test for TSCI compressed by the state-of-the-art versatile video coding (VVC) standard. By comparing the JND experimental results, the superiority and the significance of the S-JND have been demonstrated. The study results proved that semantic information is crucial for the TSCI and the S-JND is more consistency with the perception of human eyes. The newly established TSCI database as well as the related S-JND levels can be further applied to enhance perceptual visual quality in the context of image compression.

Submission Number: 4910