Blind image quality evaluation metrics design for UAV photographic application
Vision based computation of the moving CCD camera in an outdoor environment is one of the most difficult tasks in the computer vision (CV) research field. Currently, to implement only one CV function steadily, one even needs to develop a series of algorithms to meet the computational requirement of the complex environment change inevitably. So the choice of the switch occasion of these different algorithms for an abrupt change of the imaging definition is a problem. In this paper, we propose to use the Image Quality (IQ) as a measurement to find proper switch occasions of different CV algorithms for the outdoor robot system. Firstly we define three IQ metrics to describe the imaging definition of a CCD camera. Then we present an ARMA-ARCH model based multiple flows method to detect the abrupt change of these series. Finally, we use our method to cut the image sequence into multiple segments, which are fit to be processed by different CV algorithms. Many experiment results have shown the validity of our method.