With the rapid development of digital technology, the development speed of digital media is also relatively fast. Digital media technology has a great impact on people’s lifestyles and aesthetic concepts, and it also has a greater impact on visual art, creative thinking communication methods, and expression methods. In this study, the quality enhancement of digital images has been intensively studied based on the guidance of big data of eye-movement gaze points. A large amount of visual data are collected from public social resources, and the optimization research of image sensory quality is carried out in-depth using the acquired big data. Next, the region of interest (ROI) is obtained by combining the data with a two-dimensional Gaussian distribution model-fitting method, and the obtained data clustered and improved based on the K-means clustering algorithm to obtain ROI fixation points. Finally, discontinuities in the choice of sharpness in graphics and video playback are pointed out, and the final fixation data analysis is utilized. Results show that targeted optimization is very effective in improving the quality of digital images and saving space, enabling users to enjoy higher-quality visual digital images. The proposed method can be used to improve the dynamic resolution of images and videos.