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A new research on contrast sensitivity function in 3D space

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Abstract

In this paper, it tries to extend the characteristics of human eyes’ contrast sensitivity Function(CSF) into (3D) space, but the experimental results show that the traditional characteristics of CSF have limitations in 3D space for lack of depth information. In order to investigate the characteristics of CSF in 3D space, traditional CSF tests are further developed to measure the corresponding properties of CSF with different inclined planes, and describe the 𝜃−C S F characteristics of human eyes based on the inclined angles 𝜃. According to the tests, the mathematical expression of 𝜃−C S F is built up. In addition, the concept of spatial frequency in the direction of depth (f D ) is proposed, and f D −C S F characteristic surface is also achieved. The proposed 3D CSF has significant effects on the research of human visual characteristics and 3D image processing.

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References

  1. Arundale K (1978) An investigation into the variation of human contrast sensitivity with age and ocular pathology. Br J Ophthalmol 62:213–215

    Article  Google Scholar 

  2. Bodis-Wollner I, Diamond SP (1976) The measurement of spatial contrast sensitivity in cases of blurred vision associated with cerebral lesions. J Neurol 99:695–710

    Google Scholar 

  3. Bradley AP (1999) A wavelet visible difference predictor. IEEE Trans Image Process 8(5):717–730

    Article  Google Scholar 

  4. Brand\(\tilde {\alpha }\) T, Queluz MP (2010) No-reference quality assessment of h. 264/AVC encoded video. IEEE Trans Circuits Syst Video Technol 20(11):1437–1447

  5. Chen Y, Blum RS (2009) A new automated quality assessment algorithm for image fusion. Image Vis Comput 27(2)

  6. Chen H, Guillemot C (2010) Perceptually-friendly H.264/AVC video coding based on foveated just-noticeable-distortion model. IEEE Trans Circuits Syst Video Technol 20(6)

  7. Chen H, Varshney PK (2007) A human perception inspired quality metric for image fusion based on regional information. Information Fusion 8(2):193–207

    Article  Google Scholar 

  8. Chen WD, Weisi L, Bu-Sung L, Chiew TL (2012) Robust image coding based upon compressive sensing. IEEE Trans Multimedia 14(2):278–290

    Article  Google Scholar 

  9. Damera-Venkata N, Kite TD, Geisler WS et al (2000) Image quality assessment based on a degradation model. IEEE Trans Image Process 9(4):636–650

    Article  Google Scholar 

  10. Gaddipatti A, Machiraju R, Yagel R (1997) Steering image generation with wavelet based perceptual metric. Comput Graphics Forum 16(3):C241–C251

    Article  Google Scholar 

  11. Gao X, Lu W, Tao D, Li X (2009) Image quality assessment based on multiscale geometric analysis. IEEE Trans Image Process 18(7):1409–1423

    Article  MathSciNet  Google Scholar 

  12. Imamoglu N, Lin W, Fang Y (2013) A saliency detection model using low-level features based on wavelet transform. IEEE Trans Multimedia 15(1):96–105

    Article  Google Scholar 

  13. James L, Mannos DJ (1974) Sakrison the effects of a visual fidelity criterion on the encoding of images. IEEE Trans Inf Theory IT-20(4):525–536

    MATH  Google Scholar 

  14. Jayant N, Johnston J, Safranek R (1993) Signal compression based on models of human perception. Proc IEEE 81(10):1385–1422

    Article  Google Scholar 

  15. Jung S-W, Ko S-J (2012) Depth sensation enhancement using the just noticeable depth difference. IEEE Trans Image Process 21(8):3624–3637

    Article  MathSciNet  Google Scholar 

  16. Lang M, Hornung A, Wang O et al (2010) Nonlinear disparity mapping for stereoscopic 3D. ACM Trans Graph 29(4):75

    Article  Google Scholar 

  17. Li S, Zhang F, Ma L, Ngi Ngan K (2011) Image quality assessment by separately evaluating detail losses and additive impairments. IEEE Trans Multimedia 13(5):935–949

    Article  Google Scholar 

  18. Li P, Wang M, Cheng J, Xu C, Lu H (2013) Spectral hashing with semantically consistent graph for image indexing. IEEE Trans Multimedia 15(1):141–152

    Article  Google Scholar 

  19. Liu F, Niu Y, Jin H (2013) Casual stereoscopic photo authoring. IEEE Trans Multimedia 15(1): 129–140

    Article  Google Scholar 

  20. Mller K, Merkle P (2011) Thomas wiegand, 3-D video representation using depth maps. Proc IEEE 99(4):643–656

    Article  Google Scholar 

  21. Mocan MC, Najera-Covarrubias M, Wright KW (2005) Comparison of visual acuity levels in pediatric patients with Amblyopia using Wright Figures((c)), Allen Optotypes, and Snellen Letters. J AAPOS 9:48–52

    Article  Google Scholar 

  22. Nadenau MJ, Reichel J, Kunt M (2003) Wavelet-based color image compression: exploiting the contrast sensitivity function. IEEE Trans Image Process 12(1)

  23. Ng K-T, Zhu Z-Y, Wang C, Chan S-C, Shum H-Y (2012) A multi-camera approach to image-based rendering and 3-D/multiview display of ancient chinese artifacts. IEEE Trans Multimedia 14(6): 1631–1641

    Article  Google Scholar 

  24. Schade (1956) Optical and photoelectric analog of the eye. J Opt Soc Am 46 (9):721–738

    Article  Google Scholar 

  25. Shao F, Jiang G, Yu M, Chen K, Ho Y-S (2012) Asymmetric coding of Multi-View video plus depth based 3-D video for view rendering. IEEE Trans Multimedia 14(1):157–167

    Article  Google Scholar 

  26. Smolic A, Kauff P, Knorr S, Hornung A et al (2011) Three-dimentional video postproduction and processing. Proc IEEE 99(4):607–625

    Article  Google Scholar 

  27. Tao D, Li X, Lu W, Gao X (2009) Reduced-reference IQA in contourlet domain. IEEE Trans Syst Man Cybern B Cybern 39(6)

  28. Wei ZY, Ngan KN (2009) Spatio-temporal just noticeable distortion profile for grey scale image/video in DCT domain. IEEE Trans Circuits Syst Video Technol 19 (3):337–346

    Article  Google Scholar 

  29. Wei W, Yong Q (2011) Information potential fields navigation in wireless Ad-Hoc sensor networks[J]. Sensors 11(5):4794–4807

    Article  Google Scholar 

  30. Wei W, Yang X L, Shen PY et al (2012) Holes detection in anisotropic sensornets: topological methods[J]. Int J Distrib Sens Netw 2012

  31. Wei W, Yang XL, Zhou B et al (2012) Combined energy minimization for image reconstruction from few views[J]. Math Probl Eng 2012

  32. Wei W, Qin X, Wang L et al (2014) GI/Geom/1 queue based on communication model for mesh networks[J]. Int J Commun Syst 27(11):3013–3029

    Google Scholar 

  33. Wu G-L, Wu T-H, Chien S-Y (2011) Algorithm and Architecture Design of Perception Engine for Video Coding Applications. IEEE Trans Multimedia 13(6)

  34. Xing L, You J, Ebrahimi T, Perkis A (2012) Assessment of stereoscopic crosstalk perception. IEEE Trans Multimedia 14(2):326–337

  35. Yan B, Zhou J (2012) Efficient frame concealment for depth image-based 3-D video transmission. IEEE Trans Multimedia 14(3):936–941

  36. Zeng W, Daly S, Lei S (2002) An overview of the visual optimization tools in JPEG 2000. Signal Process Image Commun 17(1):85–104

    Article  Google Scholar 

  37. Zhang F, Ma L, Li S, Ngi Ngan K (2011) Practical image quality metric applied to image coding. IEEE Trans Multimedia 13(4)

Download references

Acknowledgments

This research is supported by the National Natural Science Foundation of China (No. 61471260 and No.61271324), and Program for New Century Excellent Talents in University (NCET-12-0400).

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Authors and Affiliations

  1. School of Electronic Information Engineering, Tianjin University, Tianjin, People’s Republic of China

    Jiachen Yang, Zhiqun Gao & Yancong Lin

  2. School of Optometry, University of California, Berkeley, CA, USA

    Yun Liu

  3. School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, Shanxi, China

    Wei Wei

  4. Department of Computer Science, School of Science, Loughborough University, Loughborough, UK

    Qinggang Meng

Authors
  1. Jiachen Yang
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  2. Yun Liu
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  3. Wei Wei
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  4. Qinggang Meng
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  5. Zhiqun Gao
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  6. Yancong Lin
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Correspondence to Yun Liu.

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Yang, J., Liu, Y., Wei, W. et al. A new research on contrast sensitivity function in 3D space. Multimed Tools Appl 76, 11127–11142 (2017). https://doi.org/10.1007/s11042-016-3541-9

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  • DOI: https://doi.org/10.1007/s11042-016-3541-9

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