Multi-focal Image Fusion with Convolutional Sparse Representation and Stationary Wavelet Transform

被引:1
作者
Pawar, Gandhali A. [1 ]
Kadam, Sujata [1 ]
机构
[1] RAIT, Navi Mumbai, India
来源
COMPUTING, COMMUNICATION AND SIGNAL PROCESSING, ICCASP 2018 | 2019年 / 810卷
关键词
Image fusion; Convolutional sparse representation; Stationary wavelet transform; Minute loss prevention; Shift tolerance; FOCUS IMAGES;
D O I
10.1007/978-981-13-1513-8_88
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper illustrates a completely unique technique of multi-focus image fusion involving Stationary Wavelet Transform (SWT) and Convolutional Sparse Representation (CSR). Sparse-based fusion strategies do not retain information representation and cannot tolerate minor mistakes in registration. The SWT method does not have these issues. Multi-focus image fusion is the fusion of different parts of digital images, representing the common scene, in order to produce an image with everything in Focus, i.e., without the blur effect. Camera processors cannot fuse images by themselves. Thus, experts have to employ image editing methods to obtain clear photographs. The scheme stated in this paper uses SWT to distinguish focus levels accurately. The results suggest that the strategy is successful in ways comparable in terms of visual quality and clarity.
引用
收藏
页码:865 / 873
页数:9
相关论文
共 16 条
[1]   Fusion of multi-focus images using differential evolution algorithm [J].
Aslantas, V. ;
Kurban, R. .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (12) :8861-8870
[2]  
Burt P. J., 1993, [1993] Proceedings Fourth International Conference on Computer Vision, P173, DOI 10.1109/ICCV.1993.378222
[3]   Multi-Focus Image Fusion Based on Spatial Frequency in Discrete Cosine Transform Domain [J].
Cao, Liu ;
Jin, Longxu ;
Tao, Hongjiang ;
Li, Guoning ;
Zhuang, Zhuang ;
Zhang, Yanfu .
IEEE SIGNAL PROCESSING LETTERS, 2015, 22 (02) :220-224
[4]   Image fusion: Advances in the state of the art [J].
Goshtasby, A. Ardeshir ;
Nikolov, Stavri .
INFORMATION FUSION, 2007, 8 (02) :114-118
[5]   Fusion of multi-exposure images [J].
Goshtasby, AA .
IMAGE AND VISION COMPUTING, 2005, 23 (06) :611-618
[6]   Gradient field multi-exposure images fusion for high dynamic range image visualization [J].
Gu, Bo ;
Li, Wujing ;
Wong, Jiangtao ;
Zhu, Minyun ;
Wang, Minghui .
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2012, 23 (04) :604-610
[7]   MULTISENSOR IMAGE FUSION USING THE WAVELET TRANSFORM [J].
LI, H ;
MANJUNATH, BS ;
MITRA, SK .
GRAPHICAL MODELS AND IMAGE PROCESSING, 1995, 57 (03) :235-245
[8]   Pixel-level image fusion: A survey of the state of the art [J].
Li, Shutao ;
Kang, Xudong ;
Fang, Leyuan ;
Hu, Jianwen ;
Yin, Haitao .
INFORMATION FUSION, 2017, 33 :100-112
[9]   Image matting for fusion of multi-focus images in dynamic scenes [J].
Li, Shutao ;
Kang, Xudong ;
Hu, Jianwen ;
Yang, Bin .
INFORMATION FUSION, 2013, 14 (02) :147-162
[10]  
Liu Y., IEEE IMAGE FUSION CO