DocumentCode :
709691
Title :
Layered perceptual representation for shadow vision: From detection to removal
Author :
Cheng Li ; Jing Gao ; Yanbin Shi ; Qingshun Han
Author_Institution :
Aviation Univ. of Air Force, Changchun, China
fYear :
2015
fDate :
17-18 Jan. 2015
Firstpage :
59
Lastpage :
63
Abstract :
On the research of shadow essence and visual scheme, we propose a single image shadow removal method based on certain layered perceptual representation models with the flowchart from shadow detection to shadow removal. Firstly, a modified intersecting cortical model, the typically useful image factorization technique, is applied to extract umbra and penumbra masks. Then, under the energy minimization framework, scale factors for umbra are computed. Furthermore, transparency-coupled atmospheric transfer function is introduced for penumbra compensation by pixel-by-pixel transparency estimation. For aerial images, experimental results illustrate that shadow regions are matted well, and the proposed method yields vivid shadow-free images with smooth boundaries.
Keywords :
computer vision; feature extraction; flowcharting; image representation; transfer functions; transparency; energy minimization framework; flowchart; image factorization technique; image shadow removal method; layered perceptual representation models; modified intersecting cortical model; penumbra mask extraction; pixel-by-pixel transparency estimation; shadow detection; shadow essence; shadow vision; transparency-coupled atmospheric transfer function; umbra scale factors; visual scheme; vivid shadow-free images; Atmospheric modeling; Ear; Filtering; Image restoration; Optical filters; Optical imaging; atmospheric transfer function; layered perceptual representation; shadow detection; shadow removal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Internet of Things (ICIT), 2014 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4799-7533-4
Type :
conf
DOI :
10.1109/ICAIOT.2015.7111538
Filename :
7111538
Link To Document :
بازگشت