12 March 2002 View-dependent approach to MIP for very large data
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Abstract
A simple and yet useful approach to visualize a variety of structures from sampled data is the Maximum Intensity Projection (MIP). Higher valued structures of interest pass in the projection over occluding structures. This can make MIP images difficult to interpret due to the loss of depth information. Animating about the data is one key way to try to decipher such ambiguities. The challenge is that MIP is inherently expensive and thus high frame rates are difficult to achieve. Variations to the original MIP algorithm and classification can help to further alleviate ambiguities and also provide improved image quality and very different visualizations. But they make the technique even more expensive. In addition, they require much parameter searching and tweaking. As today's data sizes are increasingly getting larger, current methods only allow very limited interaction. We explore a view-dependent approach using concepts from image-based rendering. A novel multi-layered image representation storing scalar information is computed at a view sample and then warped to the user's view. We present algorithms using OpenGL to quickly compute MIP and its variations using commodity off-the-shelf graphics hardware to achieve near interactive rates.
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Naeem Shareef, Naeem Shareef, Roger Crawfis, Roger Crawfis, } "View-dependent approach to MIP for very large data", Proc. SPIE 4665, Visualization and Data Analysis 2002, (12 March 2002); doi: 10.1117/12.458784; https://doi.org/10.1117/12.458784
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