This paper proposes and develops a saliency map suitable for the wide angle fovea (WAF) sensor. The saliency map is well-known as a computational method inspired from the human cognitive vision processing. This bottom-up processing method is often available for finding a target, which should be paid attention to, automatically from the arbitrary scene. However, it is not necessarily sufficient to use the existing saliency sap directly with the W A F sensor. Usually, we utilize the W A F sensor by combining different-level image processing tasks using its high spatial resolution central field of view (FOV) or its wide-angle F O V cooperatively, because the W A F sensor does not provide with a uniform resolution input image. When we apply the saliency map for the input image by the W A F sensor, we need to take into account unique properties of this biologically-inspired special vision sensor. Therefore, we design a novel saliency map model which is more suitable for the W A F sensor. After configuration of this specific saliency map, some verification experiments were implemented to enhance advantages of our proposed saliency map for the W A F sensor, i.e., W A F saliency map.