<p>Street advertisements, as an important component of urban landscapes, implicitly convey the economic conditions and social status of different regions through their visual features. This implicit inequality in information not only depends on the type and content of the advertisements but is also directly influenced by their visual features. However, previous studies have mainly focused on analyzing the differences in the content, type, and quantity of advertisements across communities with varying economic levels, while less attention has been given to the disparities in the visual features of advertisements across such communities. To address this issue, this study uses street view images from sample points in Xi’an and applies computer vision techniques to identify and calculate the salience, area, brightness, contrast, and color difference of advertisements. Finally, statistical methods and correlation analysis, combined with housing price data from the sample points, are used to analyze the relationship between advertisement visual features and community housing prices. The study results indicate that: The results of the Tukey Honestly Significant Difference post-hoc test indicate that the salience and area of advertisements are significantly higher in high-price communities compared to low-price communities (<i>p</i> &lt; 0.01). In contrast, the color difference between advertisements and their background is significantly greater in low-price communities than in high-price communities (<i>p</i> &lt; 0.05). The results of the correlation analysis further support these findings, showing a significant positive correlation between advertisement salience, area, and housing prices (<i>p</i> &lt; 0.01).</p>