발간년도 : [2018]
| 논문정보 |
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| 논문명(한글) |
[Vol.13, No.5] Fog Effect Generation from Approximated Image Depth |
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| 논문투고자 |
Won-Yong Lee |
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| 논문내용 |
Fog is a natural phenomenon in which light is scattered by an atmospheric aerosol. Fog effects rendering is used for games or image synthesis, as well as for special effects in movies or many digital contents. For realistic fog effects generation, depth-altitude information is essential; However, two-dimensional (2D) images generally do not have depth information, and thus fog effects are expressed simply with white color and blending, and it cause artifacts such as the shower door effect. In addition, although we can consider depth information for the effects, it has a limitation in that the SW only takes a specific type of input image that has depth information. In this paper, we propose a novel technique for generating fog effects on a two-dimensional (2D) inputted image based on the atmosphere scattering model. For this, we extract approximated depth information from the 2D input image, then, we apply the Beer-Lambert law based on approximated depth and altitude information. Based on our method, we can express fog effect onto 2D images easly and quickly and it can efficiently express various fog effects and generate natural fog effect animations. |
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