Information processing for image sensing under unfavorable photographic conditions

We investigate the problem of image sensing under unfavorable photographic conditions in a wireless image sensor network. In the scenes with deflective and/or reflective medium such as fogs, mirrors, glasses, degraded images are captured by those image sensors. Such degraded images often lack perceptual vividness and they offer a poor visibility of the scene contents. Notably, computation-intensive method to recover a better image based on single image [2] may not be applicable for wireless image sensors due to the limited computation capacities and the limited power resources (batteries) typically equipped at those wireless image sensors. In this paper, we propose a framework to recover better images under unfavorable photographic conditions in a wireless image sensor network, where a light-weighted computation method based on multiple images is employed to recover better images. Toward the realization of the whole system, we have built image sensor prototypes with commodity cameras and we validated our approach by indepth analysis, extensive simulations and field experiments in real-world situations.