Volume 34 Issue 09
Sep.  2008
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Sun Yanchun, Ma Qishuang, Liu Yueming, et al. Application of improved PCA to thermal wave image processing[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(09): 1012-1015. (in Chinese)
Citation: Sun Yanchun, Ma Qishuang, Liu Yueming, et al. Application of improved PCA to thermal wave image processing[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(09): 1012-1015. (in Chinese)

Application of improved PCA to thermal wave image processing

  • Received Date: 06 Aug 2007
  • Publish Date: 30 Sep 2008
  • To solve the problems less valid data in thermal infrared imager, uneasy dipartite corrosion area in image and lower the signal to noise ratio which happened in detection of structure parts- hidden corrosion by thermal wave imaging, the improved PCA (principal component analysis) based on the wavelet was presented. The every frame image was transformed by dyadic discrete wavelet and the characteristic of wavelet transform coefficient was analyzed. Low frequency coefficients were analyzed by fast principal component method which quoted Gram-Schmidt orthonormalization procedure in fixed-point algorithm then distilled principal component and reconstructed the low frequency coefficients. To suppress image noise, the high frequency coefficients were equated to zero. The experimental results indicated that the method made best of thermal infrared imager-s dada, improved the contrast of infrared thermal image and reduced noise of infrared thermal image, and that the method-s compute-time was short.

     

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