Fahad Fazal Elahi Guraya

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A video sequence is more than a sequence of still images. It contains a strong spatial–temporal correlation between the regions of consecutive frames. The most important characteristic of videos is the perceived motion foreground objects across the frames. The motion of foreground objects dramatically changes the importance of the objects in a scene and(More)
In this paper we study image distortions and impairments that affect the perceived quality of blackboard lectures images. We also propose a novel reference free image quality evaluation metric that correlates well with the perceived image quality. The perceived quality of images of blackboard lecture contents is mostly affected by the presence of noise,(More)
Visual attention models (VAM) try to mimic the human visual system in distinguishing salient regions from non-salient ones in the scene. Only a few attention models propose to detect salient motion in surveillance videos. These model utilizes static features such as color, intensity, orientation, face, and dynamic features such as motion to detect most(More)
Visual saliency models(VSM) mimic the human visual system to distinguish the salient regions from the non-salient ones in an image or video. Most of the visual saliency model in the literature are static hence they can only be used for images. Motion is important information in case of videos that is not present in still images and thus not used in most of(More)
Human Visual System (HVS) tends to focus on certain regions of an images or video frames. These regions form the saliency map, which could be used to better estimate the perceived quality of an image/video. In this paper, we propose a novel objective video quality metric based on these salient regions. This metric estimates the degree of blur and blockiness(More)
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