Paper Info
Title
Generation of all-in-focus images by noise-robust selective fusion of limited depth-of-field images.
Abstract
The limited depth-of-field of some cameras prevents them from capturing perfectly focused images when the imaged scene covers a large distance range. In order to compensate for this problem, image fusion has been exploited for combining images captured with different camera settings, thus yielding a higher quality all-in-focus image. Since most current approaches for image fusion rely on maximizing the spatial frequency of the composed image, the fusion process is sensitive to noise. In this paper, a new algorithm for computing the all-in-focus image from a sequence of images captured with a low depth-of-field camera is presented. The proposed approach adaptively fuses the different frames of the focus sequence in order to reduce noise while preserving image features. The algorithm consists of three stages: 1) focus measure; 2) selectivity measure; 3) and image fusion. An extensive set of experimental tests has been carried out in order to compare the proposed algorithm with state-of-the-art all-in-focus methods using both synthetic and real sequences. The obtained results show the advantages of the proposed scheme even for high levels of noise.
Year
DOI
Venue
2013
10.1109/TIP.2012.2231087
IEEE Transactions on Image Processing
Keywords
Field
DocType
algorithms,noise reduction,spatial frequency,image fusion,noise,wavelet transforms,noise measurement,signal to noise ratio
Computer vision,Pattern recognition,Image fusion,Image processing,Image quality,Image formation,Image noise,Artificial intelligence,Image restoration,Digital image processing,Image resolution,Mathematics
Journal
Volume
Issue
ISSN
22
3
1941-0042
Citations 
PageRank 
References 
33
1.21
10
Authors
4
Name
Order
Citations
PageRank
Said Pertuz1796.37
Domenec Puig233254.33
Miguel Ángel Garcia322024.41
Andrea Fusiello4147099.31