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A Efficient Image Separation Scheme Using ICA with New Fast EM algorithm
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  • A Efficient Image Separation Scheme Using ICA with New Fast EM algorithm
  • A Efficient Image Separation Scheme Using ICA with New Fast EM algorithm
저자명
Oh. Bum-Jin,Kim. Sung-Soo,Kang. Jee-Hye
간행물명
퍼지 및 지능시스템학회 논문지
권/호정보
2004년|14권 5호|pp.623-629 (7 pages)
발행정보
한국지능시스템학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

In this paper, a Efficient method for the mixed image separation is presented using independent component analysis and the new fast expectation-maximization(EM) algorithm. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme in various applications. However, it has been known that ICA does not establish good performance in source separation by itself. So, Innovation process which is one of the methods that were employed in image separation using ICA, which produces improved the mixed image separation. Unfortunately, the innovation process needs long processing time compared with ICA or EM. Thus, in order to overcome this limitation, we proposed new method which combined ICA with the New fast EM algorithm instead of using the innovation process. Proposed method improves the performance and reduces the total processing time for the Image separation. We compared our proposed method with ICA combined with innovation process. The experimental results show the effectiveness of the proposed method by applying it to image separation problems.