Abstract
  Fog, haze and smoke that degrade the scene images are caused by the 
airlight which is the ambient light absorbed and scattered in the 
atmosphere before it reaches the camera. The further the object away 
from the camera, the fainter the object in the scene. This degradation 
causes images to lose contrast and color precision which is annoying 
for many applications in computer vision such as feature detection, 
object recognition, photometric analysis, surveillance system, etc. 
Therefore, image haze removal has attracted a growing interest 
recently. Since the haze effect highly depends on the distance between 
the object in the scene and the camera, how to estimate an accurate 
depth map is a challenging issue. Many different approaches were 
proposed including single image dehazing, multiple image dehazing, and 
some algorithms with additional information and user input. With the 
developments of dehazing techniques, both amateur and commercial 
photographers benefit a lot for various purposes. In this talk, recent 
researches related to image dehazing will be reviewed and some possible 
future directions will also be discussed.

Short Biography
Ming-Sui Lee received her B.S. degree in mathematical sciences from 
National Cheng-Chi University, Taiwan, in 1999. Then she received the 
M.S. degree in electrical engineering from the University of 
California, Los Angeles (UCLA) and the Ph.D. degree in electrical 
engineering from the University of Southern California (USC) in 2002 
and 2006, respectively. Now she serves as an assistant professor at 
the Department of Computer Science and Information Engineering, 
National Taiwan University. Her research interests include 
image/video mosaicking, compressed-domain image/video processing, 
and super resolution techniques.