Volume rendering with multidimensional peak finding

摘要: Peak finding provides more accurate classification for direct volume rendering by sampling directly at local maxima in a transfer function, allowing better reproduction of high-frequency features. However, the 1D peak technique does not extend to higherdimensional classification. In this work, we develop new method with multidimensional functions, which looks peaks along image ray. We use piecewise approximations dynamically sample function space between world-space samples. As unidimensional finding, approach is useful specifying functions greater precision, and accurately noisy data lower rates. Multidimensional produces comparable quality order-of-magnitude performance, can reproduce features omitted entirely standard With no precomputation or storage requirements, it an attractive alternative preintegration functions.