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Quantifying image distortion based on Gabor filter bank and multiple regression analysis

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Abstract
Image quality assessment is indispensable for image-based applications. The approaches towards image quality assessment fall into two main categories: subjective and objective methods. Subjective assessment has been widely used. However, careful subjective assessments are experimentally difficult and lengthy, and the results obtained may vary depending on the test conditions. On the other hand, objective image quality assessment would not only alleviate the difficulties described above but would also help to expand the application field. Therefore, several works have been developed for quantifying the distortion presented on a image achieving goodness of fit between subjective and objective scores up to 92%. Nevertheless, current methodologies are designed assuming that the nature of the distortion is known. Generally, this is a limiting assumption for practical applications, since in a majority of cases the distortions in the image are unknown. Therefore, we believe that the current methods of image quality assessment should be adapted in order to identify and quantify the distortion of images at the same time. That combination can improve processes such as enhancement, restoration, compression, transmission, among others. We present an approach based on the power of the experimental design and the joint localization of the Gabor filters for studying the influence of the spatial/frequencies on image quality assessment. Therefore, we achieve a correct identification and quantification of the distortion affecting images. This method provides accurate scores and differentiability between distortions.
Keywords
Gabor filter bank, Image quality assessment, multiple linear regression

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Chicago
Ortiz Jaramillo, Benhur, Julio Cesar Garcia Alvarez, Hartmut Führ, Sergio Alejandro Orjuela Vargas, German Castellanos Dominguez, and Wilfried Philips. 2012. “Quantifying Image Distortion Based on Gabor Filter Bank and Multiple Regression Analysis.” In Proceedings of SPIE, the International Society for Optical Engineering, ed. Frans Gaykema and Peter D Burns. Vol. 8293. Bellingham, WA, USA: SPIE, the International Society for Optical Engineering.
APA
Ortiz Jaramillo, B., Garcia Alvarez, J. C., Führ, H., Orjuela Vargas, S. A., Castellanos Dominguez, G., & Philips, W. (2012). Quantifying image distortion based on Gabor filter bank and multiple regression analysis. In F. Gaykema & P. D. Burns (Eds.), Proceedings of SPIE, the International Society for Optical Engineering (Vol. 8293). Presented at the Image quality and system performance IX, Bellingham, WA, USA: SPIE, the International Society for Optical Engineering.
Vancouver
1.
Ortiz Jaramillo B, Garcia Alvarez JC, Führ H, Orjuela Vargas SA, Castellanos Dominguez G, Philips W. Quantifying image distortion based on Gabor filter bank and multiple regression analysis. In: Gaykema F, Burns PD, editors. Proceedings of SPIE, the International Society for Optical Engineering. Bellingham, WA, USA: SPIE, the International Society for Optical Engineering; 2012.
MLA
Ortiz Jaramillo, Benhur, Julio Cesar Garcia Alvarez, Hartmut Führ, et al. “Quantifying Image Distortion Based on Gabor Filter Bank and Multiple Regression Analysis.” Proceedings of SPIE, the International Society for Optical Engineering. Ed. Frans Gaykema & Peter D Burns. Vol. 8293. Bellingham, WA, USA: SPIE, the International Society for Optical Engineering, 2012. Print.
@inproceedings{2015964,
  abstract     = {Image quality assessment is indispensable for image-based applications. The approaches towards image quality assessment fall into two main categories: subjective and objective methods. Subjective assessment has been widely used. However, careful subjective assessments are experimentally difficult and lengthy, and the results obtained may vary depending on the test conditions. On the other hand, objective image quality assessment would not only alleviate the difficulties described above but would also help to expand the application field. Therefore, several works have been developed for quantifying the distortion presented on a image achieving goodness of fit between subjective and objective scores up to 92\%. Nevertheless, current methodologies are designed assuming that the nature of the distortion is known. Generally, this is a limiting assumption for practical applications, since in a majority of cases the distortions in the image are unknown. Therefore, we believe that the current methods of image quality assessment should be adapted in order to identify and quantify the distortion of images at the same time. That combination can improve processes such as enhancement, restoration, compression, transmission, among others. We present an approach based on the power of the experimental design and the joint localization of the Gabor filters for studying the influence of the spatial/frequencies on image quality assessment. Therefore, we achieve a correct identification and quantification of the distortion affecting images. This method provides accurate scores and differentiability between distortions.},
  articleno    = {82930E},
  author       = {Ortiz Jaramillo, Benhur and Garcia Alvarez, Julio Cesar  and F{\"u}hr, Hartmut and Orjuela Vargas, Sergio Alejandro and Castellanos Dominguez, German  and Philips, Wilfried},
  booktitle    = {Proceedings of SPIE, the International Society for Optical Engineering},
  editor       = {Gaykema, Frans and Burns, Peter D},
  isbn         = {9780819489401},
  issn         = {0277-786X},
  keyword      = {Gabor filter bank,Image quality assessment,multiple linear regression},
  language     = {eng},
  location     = {Burlingame, CA, USA},
  pages        = {10},
  publisher    = {SPIE, the International Society for Optical Engineering},
  title        = {Quantifying image distortion based on Gabor filter bank and multiple regression analysis},
  url          = {http://dx.doi.org/10.1117/12.912074},
  volume       = {8293},
  year         = {2012},
}

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