TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
Multiscale self-coordination of bidimensional empirical mode decomposition in image fusion |
| 영문제목(English Title) |
Multiscale self-coordination of bidimensional empirical mode decomposition in image fusion |
| 저자(Author) |
Feng-Ping An
Xian-Wei Zhou
Da-Chao Lin
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| 원문수록처(Citation) |
VOL 09 NO. 04 PP. 1441 ~ 1456 (2015. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The bidimensional empirical mode decomposition (BEMD) algorithm with high adaptability is more suitable to process multiple image fusion than traditional image fusion. However, the advantages of this algorithm are limited by the end effects problem, multiscale integration problem and number difference of intrinsic mode functions in multiple images decomposition. This study proposes the multiscale self-coordination BEMD algorithm to solve this problem. This algorithm outside extending the feather information with the support vector machine which has a high degree of generalization, then it also overcomes the BEMD end effects problem with conventional mirror extension methods of data processing, . The coordination of the extreme value point of the source image helps solve the problem of multiscale information fusion. Results show that the proposed method is better than the wavelet and NSCT method in retaining the characteristics of the source image information and the details of the mutation information inherited from the source image and in significantly improving the signal-to-noise ratio.
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| 키워드(Keyword) |
bidimensional empirical mode decomposition
multiscale
end effect
self-coordination
image fusion
peak signal-to-noise ratio
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| 파일첨부 |
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