A Real-Time Multimedia Data Quality Assessment Framework

Nowadays, social media runs a significant portion of people's daily lives. Millions of people use social media applications to share photos. The huge volume of images shared on social media presents serious challenges and requires large computational infrastructure to ensure successful data processing. However, image gets distorted somehow during the processing, transmission, sharing or from a combination of many factors. So, there is a need to guarantee an acceptable delivery content, especially for image processing applications. In this paper, we present a framework developed to process a large amount of images in real-time while estimating the image quality. Our quality evaluation is measured based on two methods: Perceptual Coherence Measure and Structural Similarity Index. A set of experiments is conducted to evaluate our proposed approach.