Feature Enhanced Visualization Algorithm for Volumetric Data

Maximum intensity difference accumulation combines the advantage of direct volume rendering and maximum intensity projection, but other features with local maximum intensity are not displayed in the final rendering image with this approach.In this paper, we present a novel feature enhanced accumulation approach to enhance features with local maximum intensity in the ray profile.Moving least squares is employed to smooth each ray profile and obtain the significant features with transition points.A local minimum-point searching method is adopted to analyze the features of the ray profile.In the rendering stage, a local intensity difference accumulation is proposed to improved integral composition of color and opacity.Also a feature analysis based surface shading is introduced to improve the spatial cues of features.Finally, Tone-reduction is employed to solve the problem that the accumulated color of the final image is beyond the luminance limitation, and preserve the original local contrast.Our approach highlight the features without complex transfer function.The experiments demonstrate the high quality rendering results of several datasets, especially from medical field.