TY - GEN
T1 - Non-referenced quality assessment of image processing methods in infrared non-destructive testing
AU - Ramírez-Rozo, Thomas J.
AU - Benítez-Restrepo, Hernan D.
AU - García-Álvarez, Julio C.
AU - Castellanos-Domínguez, German
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Blind quality assessment
KW - image quality
KW - infrared non-destructive testing
KW - natural scene statistics
UR - https://www.scopus.com/pages/publications/84884708397
U2 - 10.1007/978-3-642-41184-7_13
DO - 10.1007/978-3-642-41184-7_13
M3 - Conference contribution
AN - SCOPUS:84884708397
SN - 9783642411830
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 121
EP - 130
BT - Image Analysis and Processing, ICIAP 2013 - 17th International Conference, Proceedings
T2 - 17th International Conference on Image Analysis and Processing, ICIAP 2013
Y2 - 9 September 2013 through 13 September 2013
ER -