Domain decomposition is a popular technique for solving large computational problems that require data to be divided into smaller sub-domains. The exact manner of decomposition depends on the computational needs of the algorithm and often introduces irregular boundaries. Each subdomain forms a block of a larger grid and can be solved or rendered separately by different processing nodes. Rendering of each sub-domain can result in images which are then composited in a back-to-front or front-to-back manner. This scenario is useful when visualization is used concurrently with the simulation. However, the irregularity of boundaries may prohibit the correct image composition due to a visibility anomaly between the sub-domains. In this paper, we present an algorithm based on object-space partitioning to resolve this problem. To accelerate the partitioning process, two techniques are introduced. First, an image-space partition representation is employed for fast assignment of data points to correct partitions. Secondly, a k-d tree is used to subdivide the view-space adaptively according to the complexity of the surface. This view-space partition provides a trade-off between performance and accuracy of the rendered image. Large gains in performance can be achieved with only small losses of accuracy. Two examples of curvilinear grids of different complexity are used to demonstrate the effectiveness of this scheme. Copyright © 2005 John Wiley & Sons, Ltd.