FEATURE BASED GHOST REMOVAL IN HIGH DYNAMIC RANGE IMAGING

Hwan-Soon Sung1 , Rae-Hong Park1 , Dong-Kyu Lee1 , and SoonKeun Chang2 1Department of Electronic Engineering, School of Engineering, Sogang University, 35 Baekbeom-ro (Sinsu-dong), Mapo-gu, Seoul 121-742, Korea 2 Samsung Electronics Co., Ltd., Suwon, Gyeonggi-do 443-742, Korea 

ABSTRACT 

This paper presents a technique to reduce the ghost artifacts in a high dynamic range (HDR) image. In HDR imaging, we need to detect the motion between multiple exposure images of the same scene in order to prevent the ghost artifacts. First, we establish correspondences between the aligned reference image and the other exposure images using the zero-mean normalized cross correlation (ZNCC). Then, we find object motion regions using adaptive local thresholding of ZNCC feature maps and motion map clustering. In this process, we focus on finding accurate motion regions and on reducing false detection in order to minimize the side effects as well. Through experiments with several sets of low dynamic range images captured with different exposures, we show that the proposed method can remove the ghost artifacts better than existing methods. 

KEYWORDS 

High Dynamic Range Imaging, Ghost Removal, Motion Detection, Radiance Map Generation

More Details : http://airccse.org/journal/ijcga/papers/3413ijcga03.pdf