Volume Ray Casting quality estimation in terms of Peak Signal-to-Noise Ratio

In spite of a large number of techniques aimed for improvement of Direct Volume Rendering (DVR) quality and performance proposed in the literature, there is a lack of approaches for numerical quality estimation of the images obtained by visualization of medical and scientific volumetric datasets. In this paper we propose a method to estimate sampling artifacts in DVR. Using the proposed estimation method we compare different Ray Casting algorithms to expose optimal ones in quality-performance criteria. We also propose method which combines two techniques for sampling artifacts reduction: Preintegrated DVR and Virtual Samplings method. We show that this combination overcomes both basic methods when using local shading or/and tricubic filtering in RC algorithm