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Non–referenced Quality Assessment of Image Processing Methods in Infrared Non-destructive Testing

  • Thomas J. Ramírez-Rozo
  • Hernan D. Benítez-Restrepo
  • Julio C. García-Álvarez
  • German Castellanos-Domínguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)

Abstract

Infrared Non–Destructive Testing (IRNDT) uses several image processing techniques to enhance visual contrast and visibility of defects in inspected materials. The benchmarking of these techniques is often too qualitative due to a lack of quantitative criteria allowing to assess the qualities of the compared methods. In this work, we compare image processing techniques in IRNDT with a non–referenced (NR) image quality assessment (IQA) algorithm. Furthermore, we validate the NR IQA approach through a human–based quality evaluation and analyze statistical properties of IRNDT images. The results show a high correlation between NR IQA measure quality predictions and subjective evaluation. Moreover, the analysis evidenced a relationship of perceived image quality with 1) the spatial power spectral density, and 2) marginal and joint distributions of wavelet coefficients. This analysis provides a quantitative alternative when comparing image processing methods in IRNDT and can be used to develop specific IQA measure for IRNDT.

Keywords

Blind quality assessment image quality infrared non-destructive testing natural scene statistics 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thomas J. Ramírez-Rozo
    • 1
  • Hernan D. Benítez-Restrepo
    • 2
  • Julio C. García-Álvarez
    • 1
  • German Castellanos-Domínguez
    • 1
  1. 1.Universidad Nacional de ColombiaManizalesColombia
  2. 2.Pontificia Universidad JaverianaCaliColombia

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