Superresolution modeling using an omnidirectional image sensor

Recently, many virtual reality and robotics applications have been called on to create virtual environments from real scenes. A catadioptric omnidirectional image sensor composed of a convex mirror can simultaneously observe a 360-degree field of view making it useful for modeling man-made environments such as rooms, corridors, and buildings, because any landmarks around the sensor can be taken in and tracked in its large field of view. However, the angular resolution of the omnidirectional image is low because of the large field of view captured. Hence, the resolution of surface texture patterns on the three-dimensional (3-D) scene model generated is not sufficient for monitoring details. To overcome this, we propose a high- resolution scene texture generation method that combines an omnidirectional image sequence using image mosaic and superresolution techniques.