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To improve the response ability of calamity rescue, a developing air-space integrative system is presented. In contrast to other system, this system utilizes both the Remote Satellite System (RSS) and the Unmanned Aerial Vehicle (UAV) to implement the information collection and analysis task. Three novel functions of this system are emphasized: the people searching and positioning, the line patrolling and checking, and the delivery of rescue materials using UAV. Both the image analysis and the UAV control techniques are employed: the infrared and visible light fusion algorithm is used to detect the victims in disaster areas; the satellite navigation and vision analysis techniques are utilized to realize the line patrolling and checking; and the camera based navigation and control methods are employed to deliver the necessary rescue materials to victims. The Analytic Hierarchy Process (AHP) method is proposed to assist the decision making of calamity rescue according to the preplan database. This system is still under development and it will improve the calamity rescue ability of China in future.

A number of blind Image Quality Evaluation Metrics (IQEMs) for Unmanned Aerial Vehicle (UAV) photograph application are presented. Nowadays, the visible light camera is widely used for UAV photograph application because of its vivid imaging effect; however, the outdoor environment light will produce great negative influences on its imaging output unfortunately. In this paper, to conquer this problem above, we design and reuse a series of blind IQEMs to analyze the imaging quality of UAV application. The Human Visual System (HVS) based IQEMs, including the image brightness level, the image contrast level, the image noise level, the image edge blur level, the image texture intensity level, the image jitter level, and the image flicker level, are all considered in our application. Once these IQEMs are calculated, they can be utilized to provide a computational reference for the following image processing application, such as image understanding and recognition. Some preliminary experiments for image enhancement have proved the correctness and validity of our proposed technique.