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二維滑動(dòng)矩形窗傅氏變換的快速遞推算法

張麗飛,  楊鴻波,  王東峰,  鄒謀炎

張麗飛, 楊鴻波, 王東峰, 鄒謀炎. 二維滑動(dòng)矩形窗傅氏變換的快速遞推算法[J]. 電子與信息學(xué)報(bào), 2003, 25(10): 1334-1340.
引用本文: 張麗飛, 楊鴻波, 王東峰, 鄒謀炎. 二維滑動(dòng)矩形窗傅氏變換的快速遞推算法[J]. 電子與信息學(xué)報(bào), 2003, 25(10): 1334-1340.
Zhang Lifei, Yang Hongbo, Wang Dongfeng, Zou Mouyan. A fast recursive algorithm for the 2D sliding rectangular window FFT[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1334-1340.
Citation: Zhang Lifei, Yang Hongbo, Wang Dongfeng, Zou Mouyan. A fast recursive algorithm for the 2D sliding rectangular window FFT[J]. Journal of Electronics & Information Technology, 2003, 25(10): 1334-1340.

二維滑動(dòng)矩形窗傅氏變換的快速遞推算法

A fast recursive algorithm for the 2D sliding rectangular window FFT

  • 摘要: 該文利用相鄰滑動(dòng)窗數(shù)據(jù)之間的關(guān)系以及傅氏變換的平移性質(zhì)，提出一種二維滑動(dòng)矩形窗傅氏變換的快速遞推算法。文中分析了該快速遞推算法的復(fù)雜度和傳統(tǒng)直接計(jì)算法的復(fù)雜度，證明了新的快速遞推法可以大大降低計(jì)算復(fù)雜性，尤其是在圖像尺寸和窗口尺寸較大的場(chǎng)合中。該算法可以改善滑窗傅氏變換或Gabor變換的計(jì)算效率。
    Abstract: In this paper, a fast recursive algorithm for the 2D sliding rectangular window FFT is proposed, based on the relationship of neighbor windows and the transformation property of the FFT. Further, the fast recursive algorithm is extended into 2D Gabor transformation of sliding rectangular windows. An analysis and a comparison on the computational complexity between the recursive algorithm and the traditional direct method are given. Both the theoret-ical analysis and the experimental result show that the new recursive algorithm can reduce the computation cost greatly, especially in the case of bigger image size or/and bigger window size. The proposed recursive algorithm can improve the computation efficiency of image analysis using the slide rectangular window FFT or Gabor transform.
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  • C.H. Chen, L. F. Pau, P. S. P. Wang, Texture Analysis, In The Handbook of Pattern Recognition and Computer Vision (2nd Edition), NY, World Scientific Publishing Co., 1998, 207-248.[2]Zou Mouyan, Wang Dongfeng, Texture identification and image segmentation via Fourier transform.[J]. Proceedings for SPIE.2001,Vol. 4550:34-[3]R. Azencott, J. P. Wang, L. Younes, Texture classification using windowed Fourier filters, IEEE Trans. on Patt. Anal. Mach. Intell., 1997, 19(2), 148-153.[4]T. Randen, J. H. Husoy, Filtering for texture classification: a comparative study, IEEE Trans.on Patt. Anal. Mach. Intell., 1999, 21(4), 291-310.[5]P.S. William, The automatic hierarchical decomposition of images into sub-images for use in image recognition and classification, [PHD Thesis], The University of Western Australia, Sep.1999.[6]C.M. Chen, H. H. Lu, K. C. Han, A textural approach based on Gabor functions for texture edge detection in ultrasound images, Ultrasound in Med. Biol., 2001, 27(4), 515-534.[7]D. Puig, M. A. GarCia, Determining optimal window size for texture feature extraction methods,IX Spanish Symposium on Pattern Recognition and Image Analysis, Castellon, Spain, May 2001,vol.2, 237-242.[8]M. Koppen.[J].J. R. Solar, P. Soille, Texture segmentation by biologically-inspired use of neural networks and mathematical morphology, Proc. of the International ICSC/IFAC Symposium on Neural Computation (NC98), Vienna, Austria, September 23-2.1998,:-
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出版歷程
  • 收稿日期:  2002-02-18
  • 修回日期:  2003-03-10
  • 刊出日期:  2003-10-19

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