Journal
SIGNAL PROCESSING
Volume 138, Issue -, Pages 71-85Publisher
ELSEVIER
DOI: 10.1016/j.sigpro.2017.03.008
Keywords
Multifocus image fusion; Multiscale image analysis; Focused region detection; Non-local means filtering
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Funding
- National Natural Science Foundation of China [61302041, 61562053, 61363043]
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In multifocus image fusion, accurate detection of the focused pixel from source images is crucial to improve the quality of fused result. Traditionally, the method developed in spatial domain is commonly used. However, such approaches tend to produce boundary seams or distortions. To this end, we propose a new fixed window technique of multiscale image analysis (MIA) and a new weighted fusion strategy by employing non-local means filtering (NLF). This new scheme consists of three parts: detection of focused pixel, correction of detecting results, and generation of fusion weight maps for source images. To improve detection robustness against the size of object, we develop the fixed window technique of MIA to detect the focused pixels, and then we construct the initial fusion decision map for each of source images by combining those detection results; second, we present a new refining process based on block consistency evaluation for correcting the initial detection result. At last, the corresponding source images are used as a guide and combined with the NLF to produce the fusion weight maps. Experimental results demonstrate that the performance of our approach is superior to that of many state-of-the-art algorithms in terms of both visual perception and objective evaluation. (C) 2017 Elsevier B.V. All rights reserved.
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