Generation of All-in-Focus Images by Noise-Robust Selective Fusion of Limited Depth-of-Field Images

• Published in: IEEE transactions on image processing Vol. 22; no. 3; pp. 1242 - 1251
• Main Authors: Pertuz, S., Puig, D., Garcia, M. A., Fusiello, A.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; All-in-focus; Applied sciences; Cameras; Defense industry; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; extended depth of field; focus measure; Frequency measurement; Fuses; Image Enhancement - methods; Image fusion; Image Interpretation, Computer-Assisted - methods; Image processing; Imaging, Three-Dimensional - methods; Information, signal and communications theory; Noise; Noise measurement; Noise sensitivity; Pattern Recognition, Automated - methods; Reproducibility of Results; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal, noise; Signal-To-Noise Ratio; State of the art; Studies; Subtraction Technique; Telecommunications and information theory; Transaction processing; Wavelet transforms; Weight measurement; All-in-focus; State of the art; Image processing; Noise reduction; Selectivity; Algorithm; Adaptive method; Depth of field; Spatial frequency; extended depth of field; Image sequence; Signal processing; focus measure; Noise immunity; Image fusion
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2012.2231087

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.