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Adapting Texture Compression to Perceptual Quality Metric for Textured 3D Models

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11010))

Abstract

3D textured models are an integral part of modern computer graphics. The geometry of these models is represented by a 3D polygonal mesh and the textures by 2D images. 3D textured models occupy more storage space than conventional images, since we need to store both the mesh and the texture. Thus, they can be expensive to store and transmit. One way to reduce these costs is to compress the mesh and texture in 3D models. Compression invariably leads to the loss of visual quality. Therefore, a method for objectively measuring the perceived loss in visual quality is important. There are studies that can mathematically model the perceptual impact of 3D mesh compression. However, there are only a few studies on the perceptual impact of texture compression. In this paper, we perform a subjective experiment to measure the perceived loss of quality of a 3D model caused by JPEG compression of the model’s texture. We propose a simple modeling function that can determine the perceived quality of a 3D model with JPEG compressed texture.

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References

  1. Guilford, J.P.: Psychometric methods (1954)

    Google Scholar 

  2. Iglewicz, B., Hoaglin, D.C.: How to Detect and Handle Outliers, ASQC Basic References in Quality Control. American Society for Quality Control, Milwaukee (1993)

    Google Scholar 

  3. Larson, E.C., Chandler, D.M.: Most apparent distortion: a dual strategy for full-reference image quality assessment. In: Proceedings of SPIE, vol. 7242, pp. 72,420S–72,420S–17 (2009)

    Google Scholar 

  4. Mittal, A., Soundararajan, R., Bovik, A.C.: Making a “completely blind” image quality analyzer. Sig. Process. Lett. IEEE 20(3), 209–212 (2013)

    Article  Google Scholar 

  5. Pan, Y., Cheng, I., Basu, A.: Quality metric for approximating subjective evaluation of 3-D objects. Trans. Multimedia 7(2), 269–279 (2005). https://doi.org/10.1109/TMM.2005.843364

    Article  Google Scholar 

  6. Rogowitz, B.E., Rushmeier, H.E.: Are image quality metrics adequate to evaluate the quality of geometric objects? vol. 4299, pp. 340–348 (2001). https://doi.org/10.1117/12.429504

  7. Zhang, L., Zhang, D., Mou, X., Zhang, D.: FSIM: a feature similarity index for image quality assessment. IEEE Trans. Image Process. 20(8), 2378–2386 (2011). https://doi.org/10.1109/TIP.2011.2109730

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Navaneeth Kamballur Kottayil , Irene Cheng , Kumaradevan Punithakumar or Anup Basu .

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Kottayil, N.K., Cheng, I., Punithakumar, K., Basu, A. (2018). Adapting Texture Compression to Perceptual Quality Metric for Textured 3D Models. In: Basu, A., Berretti, S. (eds) Smart Multimedia. ICSM 2018. Lecture Notes in Computer Science(), vol 11010. Springer, Cham. https://doi.org/10.1007/978-3-030-04375-9_34

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  • DOI: https://doi.org/10.1007/978-3-030-04375-9_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04374-2

  • Online ISBN: 978-3-030-04375-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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