Abstract
In this paper, we try to extend human eyes’ contrast sensitivities characteristics (CSF) to three-dimensional space, but the experimental results show that the traditional characteristics of CSF has limitations in three-dimensional space. In order to investigate the characteristics of human eyes’ CSF in three-dimensional space, the traditional CSF test method is developed to measure the corresponding values of CSF in different inclined planes in three-dimensional space. Human visual contrast sensitivity characteristics with different inclined angles \(\theta \) are analyzed, and the mathematical expression of \(\theta -CSF\) is built up based on the experimental results. The proposed \(\theta -CSF\) model of three-dimensional space in this paper can well reflects human visual contrast sensitivity characteristics in 3D space and has significant effect on three-dimensional image processing.
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Legg, P.A., Rosin, P.L., Marshall, D., Morgan, J.E.: Feature Neighbourhood Mutual Information for Multi-Modal Image Registration: An Application to Eye Fundus Imaging. Pattern Recognition 48(6), 1937–1946 (2015)
Martinez, F., Carrasco, A., Salas, J., di Baja, G.S.: Pattern Recognition Application in Computer Vision and Image Analysis. Pattern Recognition 48(4), 1025–1026 (2015)
Smith, S., Williams, I.: A Statistical Method for Improved 3D Surface Detection. IEEE Signal Processing Letters 22(8), 1045–1049 (2015)
Wei, W., Qi, Y.: Information Potential Fields Navigation in Wireless Ad-Hoc Sensor Networks. Sensors 11(5), 4794–4807 (2011)
Peng, R.B., Varshney, P.K.: A Human Visual System-Driven Image Segmentation Algorithm. Journal of Visual Communication and Image Representation 26, 66–79 (2015)
Chang, H.W., Zhang, Q.W., Wu, Q.G., Gan, Y.: Perceptual Image Quality Assessment by Independent feature detector. Neurocomputing 151(10), 1142–1152 (2015)
Rosén, R., Lundström, L., Venkataraman, A.P., et al.: Quick Contrast Sensitivity Measurements in the Periphery. Journal of Vision 14(8) (2014)
Liu, R., Zhou, J.W., et al.: Immature Visual Neural System in Children Reflected by Contrast Sensitivity with Adaptive Optics Correction. Scientific Reports 4(4687), April 2014
Wei, Z.Y., Ngan, K.N.: Spatio-Temporal Just Noticeable Distortion Profile for Grey Scale Image/Video in DCT Domain. IEEE Transactions on Circuits and Systems for Video Technology 19(3), 337–346 (2009)
Brand\(\tilde{\alpha }\), T., Queluz, M.P.: No-Reference Quality Assessment of H.264/AVC Encoded Video. IEEE Transactions on Circuits and Systems for Video Technology 20(11), 1437–1447 (2010)
Chen, Y., Blum, R.S.: A New Automated Quality Assessment Algorithm for Image Fusion. Image and Vision Computing 27(2), September 2009
Tao, D., Li, X., Lu, W., Gao, X.: Reduced-Reference IQA in Contourlet Domain. IEEE Transaction on Systems Man and Cybernetics-Part B: Cybernatics 39(6), December 2009
Gao, X., Lu, W., Tao, D., Li, X.: Image Quality Assessment Based on Multiscale Geometric Analysis. IEEE Transactions on Image Processing 18(7), July 2009
Li, S., Zhang, F., Ma, L., Ngan, K.N.: Image Quality Assessment by Separately Evaluating Detail Losses and Additive Impairments. IEEE Transactions on Multimedia 13(5), October 2011
Zhang, F., Ma, L., Li, S., Ngan, K.N.: Practical Image Quality Metric Applied to Image Coding. IEEE Transactions on Multimedia 13(4), August 2011
Wu, G.-L., Wu, T.-H., Chien, S.-Y.: Algorithm and Architecture Design of Perception Engine for Video Coding Applications. IEEE Transactions on Multimedia 13(6), December 2011
Müller, K., Merkle, P., Wiegand, T.: 3-D Video Representation Using Depth Maps. Proceedings of the IEEE 99(4), 643–656 (2011)
Urvoy, M., Goudia, D., Autrusseau, F.: Perceptual DFT Watermarking With Improved Detection and Robustness to Geometrical Distortions. IEEE Transactions on Information Forensics and Security 9(7), 1108–1119 (2014)
Tsai, M.J., Liu, J., Yin, J.S., Yuadi, I.: A Visible Wavelet Watermarking Technique based on Exploiting the Contrast Sensitivity Function and Noise Reduction of Human Vision System. Multimedia Tools and Applicatios 72(2), 1311–1340 (2014)
Boisvert, J., Drouin, M.A., Jodoin, P.M.: High-Speed Transition Patterns for Video Projection, 3D Reconstruction, and Copyright Protection. Pattern Recognition 48(3), 720–731 (2015)
Elaiwat, S., Bennamoun, M., Boussaid, F., et al.: A Curve Let-based Approach for Textured 3D Face Recognition. Pattern Recognition 48(4), 1235–1246 (2015)
Schade, S.R.: Optical and Photoelectric Analog of the Eye. Journal of the Optical Society of America 46(9), 721–738 (1956)
Bodis-Wollner, I., Diamond, S.P.: The Measurement of Spatial Contrast Sensitivity in cases of Blurred Vision Associated with Cerebral Lesions. Journal of Neurology 99, 695–710 (1976)
Mocan, M.C., Najera-Covarrubias, M., Wright, K.W.: Comparison of Visual Acuity Levels in Pediatric Patients with Amblyopia using Wright Figures((c)), Allen Optotypes, and Snellen Letters. Journal of Aapos 9, 48–52 (2005)
Mannos, J.L., Sakrison, D.J.: The Effects of a Visual Fidelity Criterion on the Encoding of Images. IEEE Transactions on Information Theory IT-20(4), July 1974
Zeng, W., Daly, S., Lei, S.: An Overview of the Visual Optimization Tools in JPEG 2000. Signal Processing: Image Communication 17(1), 85–104 (2002)
Gaddipatti, A., Machiraju, R., Yagel, R.: Steering Image Generation with Wavelet Based Perceptual Metric. Computer Graphics Forum 16(3), C241–C251 (1997)
Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C: The Art of Scientific Computing. Cambridge Univ. Press (1992)
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Yang, J., Liu, Y., Wei, W., Meng, Q., Gao, Z., Lin, Y. (2015). A New Research on Contrast Sensitivity Function Based on Three-Dimensional Space. In: Zha, H., Chen, X., Wang, L., Miao, Q. (eds) Computer Vision. CCCV 2015. Communications in Computer and Information Science, vol 547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48570-5_40
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DOI: https://doi.org/10.1007/978-3-662-48570-5_40
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