A Novel Framework for Multi-focus Image Fusion

被引:0
作者
Bhatnagar, Gaurav [1 ]
Wu, Q. M. Jonathan [2 ]
机构
[1] Indian Inst Technol, Jodhpur, Rajasthan, India
[2] Univ Windsor, Windsor, ON N9B 3P4, Canada
来源
2013 FOURTH NATIONAL CONFERENCE ON COMPUTER VISION, PATTERN RECOGNITION, IMAGE PROCESSING AND GRAPHICS (NCVPRIPG) | 2013年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the foremost requisite for human perception and computer vision task is to get an image with all objects in focus. The image fusion process, as one of the solutions, allows getting a clear fused image from several images acquired with different focus levels of a scene. In this paper, a novel framework for multi-focus image fusion is proposed, which is computationally simple since it realizes only in the spatial domain. The proposed framework is based on the fractal dimensions of the images into the fusion process. The extensive experiments on different multifocus image sets demonstrate that it is consistently superior to the conventional image fusion methods in terms of visual and quantitative evaluations.
引用
收藏
页数:4
相关论文
共 11 条
[1]  
CHAVEZ PS, 1989, PHOTOGRAMM ENG REM S, V55, P339
[2]   A simple and efficient algorithm for multifocus image fusion using morphological wavelets [J].
De, I ;
Chanda, B .
SIGNAL PROCESSING, 2006, 86 (05) :924-936
[3]   Selection of image fusion quality measures: objective, subjective, and metric assessment [J].
Dixon, Timothy D. ;
Canga, Eduardo Fernandez ;
Nikolov, Stavri G. ;
Troscianko, Tom ;
Noyes, Jan M. ;
Canagarajah, C. Nishan ;
Bull, Dave R. .
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2007, 24 (12) :B125-B135
[4]   MULTIPLE RESOLUTION TEXTURE ANALYSIS AND CLASSIFICATION [J].
PELEG, S ;
NAOR, J ;
HARTLEY, R ;
AVNIR, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1984, 6 (04) :518-523
[5]  
Petrovic VS, 2004, IEEE T IMAGE PROCESS, V13, P228, DOI [10.1109/TIP.2004.823821, 10.1109/tip.2004.823821]
[6]  
Piella G., 2003, Information Fusion, V4, P259, DOI 10.1016/S1566-2535(03)00046-0
[7]  
Stathaki T., 2011, Image fusion: Algorithms and applications
[8]   Adaptive multi-focus image fusion using a wavelet-based statistical sharpness measure [J].
Tian, Jing ;
Chen, Li .
SIGNAL PROCESSING, 2012, 92 (09) :2137-2146
[9]   MERGING THERMAL AND VISUAL IMAGES BY A CONTRAST PYRAMID [J].
TOET, A ;
VANRUYVEN, LJ ;
VALETON, JM .
OPTICAL ENGINEERING, 1989, 28 (07) :789-792
[10]   IMAGE FUSION BY A RATIO OF LOW-PASS PYRAMID [J].
TOET, A .
PATTERN RECOGNITION LETTERS, 1989, 9 (04) :245-253