Direct volume rendering (DVR) is a powerful visualization technique which allows users to effectively explore and study volumetric datasets. Different transparency settings can be flexibly assigned to different structures such that some valuable information can be revealed in direct volume rendered images (DVRIs). However, end-users often feel that some risks are always associated with DVR because they do not know whether any important information is missing from the transparent regions of DVRIs. In this paper, we investigate how to semi-automatically generate a set of DVRIs and also an animation which can reveal information missed in the original DVRIs and meanwhile satisfy some image quality criteria such as coherence. A complete framework is developed to tackle various problems related to the generation and quality evaluation of visibility-aware DVRIs and animations. Our technique can reduce the risk of using direct volume rendering and thus boost the confidence of users in volume rendering systems.