Wu Bin, Cheng Peng. Application of General Orthogonal Polynomials on Tracking Problem of Time-varying Systems Optimal Control[J]. Journal of Beijing University of Aeronautics and Astronautics, 1999, 25(4): 414-417. (in Chinese)
Citation: Guo Xingwang, Gao Gongchen, . Infrared image sequence processing based on singular value decomposition[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(08): 937-940. (in Chinese)

Infrared image sequence processing based on singular value decomposition

  • Received Date: 08 Oct 2005
  • Publish Date: 31 Aug 2006
  • The raw thermal images acquired in infrared thermographic nondestructive testing(IT NDT) usually have low signal-to-noise ratio(SNR) and temperature contrast. In order to restrain the bad effects of noise, singular value decomposition(SVD) technique was used in infrared image sequence processing to yield high defect contrast for digital images reconstructed in IT NDT and to improve the flaw detectivity, and its validity was illustrated by examples. The principle of SVD was introduced. The SVD method was used to process the infrared image sequences obtained in experiments. The image processing effect was quantitatively evaluated by SNR. The research indicates that SVD has the ability of extracting the algebra characteristics which reflect the underlying structural flaw in a sample. It can remove the uneven heating effect and increase the SNR of images, and the defect location in images doesn′t affect the practical efficacy of SVD. Thus SVD is an effective method for IR digital image sequence processing in IT NDT.

     

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