The human visual system (HVS) seeks toward select relevant region in the direction of level rear method attempts. visual concentration effort to guess the essential region of films or imagery observed through an individual eye. Such representations, are functioned to areas similar to workstation work, MPEG conventions, and an eminence evaluation. while numerous models are expected, only some of them be pertinent enroute for high dynamic range (HDR) picture substance, in addition to no effort has been completed for HDR visualization. Furthermore, the disadvantage inside the obtainable form is with the intention, they couldn't reproduce the uniqueness of HVS beneath the extensive shining array established in HDR substance. This paper gets the better of these troubles by the process approach to represent the bottom-up visual saliency for HDR input through merge spatial and temporal image features. An examine of a human eye ball movement information make sure the efficiency of the proposed model. Evaluation using 3 well-known quantitative metrics show that the proposed model significantly gets better predictions of visual concentration for HDR substance.