In spite of technological advances in wireless systems, transmitted data suffers from impairments through both lossy source coding and transmission overerror prone channels. Due to these errors, the quality of multimedia content is degraded. The major challenge for service providers in this scenario is to measure the perceptual impact of distortions to provide certain Quality of Experience(QoE) to the end user. The general tendency of the Human Visual System (HVS) suggests that the artifacts in the Region-of-Interest (ROI) are perceived to be more annoying compared to the artifacts in Background (BG). With this assumption, the thesis aims to measure the quality of image over ROI and BG independently. Visual Information Fidelity (VIF), a full-reference image quality assessment is chosen for this purpose. Finally, the metric measured over ROI and BG are pooled to get a ROI aware metric. The ROI aware metric is used to predict the Mean Opinion Score (MOS) of an image. In this study, an ROI aware quality metric is used to measure the quality of a set of distorted images generated using a wireless channel. Eventually, MOS of the distorted images is estimated. Lastly, the predicted MOS is validated with the MOS obtained from subjective tests. Testing the proposed image quality assessment approach shows an improved prediction performance of ROI aware quality metric over traditional image quality metrics. It is also observed that the above approach provides a consistent improvement over a wide variety of distortions. After extensive research, the obtained results suggest that the impairments in the ROI are perceived to be more annoying than that of the BG.