Abstract
Realistic rendering of foggy scene is important in game development and virtual reality. Traditional methods have many parameters to control or require a long time to compute, and they are usually limited to depicting a homogeneous fog without considering the foggy scene with heterogeneous fog. In this paper, a new rendering method based on transmission map estimation is proposed. We first generate perlin noise image as the density distribution texture of heterogeneous fog. Then we estimate the transmission map using the Markov random field (MRF) model and the bilateral filter. Finally, virtual foggy scene is realistically rendered with the generated perlin noise image and the transmission map according to the atmospheric scattering model. Experimental results show that the rendered results of our approach are quite satisfactory.
Highlights
Visualization of atmospheric phenomena is an important use of computer graphics, and among of these, fog is one of the most common scenes in game scene and virtual reality
The simulation in real-time is usually limited to depicting a homogeneous fog with constant density distribution
To render the foggy scene, we first analyze the physical characters of a foggy image, including the model that describes the formation of a foggy image and the noise used for generating heterogeneous fog
Summary
Visualization of atmospheric phenomena is an important use of computer graphics, and among of these, fog is one of the most common scenes in game scene and virtual reality. A realistic fog will greatly improve the reality of virtual scenes and add attractiveness to the generated scenes when created. Many applications of the simulated fog in computer games, virtual reality, special effects in movies and TV, and so forth can be found. In the natural world, the phenomenon is more complex It is a participating medium made of many nonhomogenous layers moving with the wind and undergoing turbulent motion. This paper discusses the problem of fog simulation and visualization, with special emphasis on generating heterogeneous fog in real-time using image processing method.
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