@article{ART002397794},
author={Won-Yong Lee},
title={Fog Effect Generation from Approximated Image Depth},
journal={Journal of Knowledge Information Technology and Systems},
issn={1975-7700},
year={2018},
volume={13},
number={5},
pages={553-560},
doi={10.34163/jkits.2018.13.5.005}
TY - JOUR
AU - Won-Yong Lee
TI - Fog Effect Generation from Approximated Image Depth
JO - Journal of Knowledge Information Technology and Systems
PY - 2018
VL - 13
IS - 5
PB - Korea Knowledge Information Technology Society
SP - 553
EP - 560
SN - 1975-7700
AB - 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.
KW - Fog rendering;Depth extraction;Image synthesis;Image segmentation;Fog animation.
DO - 10.34163/jkits.2018.13.5.005
ER -
Won-Yong Lee. (2018). Fog Effect Generation from Approximated Image Depth. Journal of Knowledge Information Technology and Systems, 13(5), 553-560.
Won-Yong Lee. 2018, "Fog Effect Generation from Approximated Image Depth", Journal of Knowledge Information Technology and Systems, vol.13, no.5 pp.553-560. Available from: doi:10.34163/jkits.2018.13.5.005
Won-Yong Lee "Fog Effect Generation from Approximated Image Depth" Journal of Knowledge Information Technology and Systems 13.5 pp.553-560 (2018) : 553.
Won-Yong Lee. Fog Effect Generation from Approximated Image Depth. 2018; 13(5), 553-560. Available from: doi:10.34163/jkits.2018.13.5.005
Won-Yong Lee. "Fog Effect Generation from Approximated Image Depth" Journal of Knowledge Information Technology and Systems 13, no.5 (2018) : 553-560.doi: 10.34163/jkits.2018.13.5.005
Won-Yong Lee. Fog Effect Generation from Approximated Image Depth. Journal of Knowledge Information Technology and Systems, 13(5), 553-560. doi: 10.34163/jkits.2018.13.5.005
Won-Yong Lee. Fog Effect Generation from Approximated Image Depth. Journal of Knowledge Information Technology and Systems. 2018; 13(5) 553-560. doi: 10.34163/jkits.2018.13.5.005
Won-Yong Lee. Fog Effect Generation from Approximated Image Depth. 2018; 13(5), 553-560. Available from: doi:10.34163/jkits.2018.13.5.005
Won-Yong Lee. "Fog Effect Generation from Approximated Image Depth" Journal of Knowledge Information Technology and Systems 13, no.5 (2018) : 553-560.doi: 10.34163/jkits.2018.13.5.005
