%0 Journal Article %A LI Kangda %A LIU Hao %A WANG Bing %A SUN Xiaofan %A ZHANG Xinsheng %T Compressive sampling allocation algorithm based on hybrid quality of image set %D 2018 %R 10.3778/j.issn.1002-8331.1707-0503 %J Computer Engineering and Applications %P 191-196 %V 54 %N 22 %X For the compressive sensing coding of an aerial image set, the current methods only allocate a regular sampling subrate for each image in the image set. Without considering the different characteristics of image scenes and the overall quality of an image set, the regular allocation mechanism is difficult to properly utilize the limited sampling resources. Under the constraint of total sampling resources, it is still an open issue how to efficiently provide a certain sampling subrate for a different image in an aerial image set. To assess the overall quality of an image set, this paper firstly proposes a hybrid quality metric according to the general requirements of an aerial image set. By evaluating the relative complexity of different aerial images, this paper establishes an image-level variation model, and then proposes a model-guided subrate allocation algorithm for different images in an image set. The experimental results show that compared with the existing methods, the proposed algorithm can significantly improve the overall quality of each aerial image set. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1707-0503