Multifocus image fusion using artificial neural networks

被引:237
|
作者
Li, ST [1 ]
Kwok, JT
Wang, YN
机构
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China
[2] Hong Kong Univ Sci & Technol, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
关键词
image fusion; neural networks; probabilistic neural networks; radial basis function networks;
D O I
10.1016/S0167-8655(02)00029-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Optical lenses, particularly those with long focal lengths, suffer from the problem of limited depth of field. Consequently, it is often difficult to obtain good focus for all objects in the picture. One possible solution is to take several pictures with different focus points, and then combine them together to form a single image. This paper describes an application of artificial neural networks to this pixel level multifocus image fusion problem based on the use of image blocks. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach, particularly when there is a movement in the objects or misregistration of the source images. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:985 / 997
页数:13
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