Abstract
A visual measure for the purpose of video compressions is proposed in this paper. The novelty of the proposed scheme relies on combining three human perception models: motion attention model, eye movement based spatiotemporal visual sensitivity function, and visual masking model. With the aid of spatiotemporal visual sensitivity function, the visual sensitivities to DCT coefficients on less attended macroblocks are evaluated. The spatiotemporal distortion masking measures at macroblock level are then estimated based on the visual masking thresholds of the DCT coefficients with low sensitivities. Accordingly, macroblocks that can hide more distortions are assigned larger quantization parameters. Experiments conducted on the basis of H.264 demonstrate that this scheme effectively improves coding efficiency without picture quality degradation.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
H.264/AVC Software, http://iphome.hhi.de/suehring/tml
Itti, L.: Automatic Foveation for Video Compression Using a Neurobiological Model of Visual Attention. IEEE Trans. Image Processing 13(10), 1304–1318 (2004)
Agrafiotis, D., Canagarajah, N., Bull, D.R., Dye, M.: Perceptually Optimized Sign Language Video Coding Based on Eye Tracking Analysis. IEE Electronics Letters 39(2), 1703–1705 (2003)
Wang, Z., Lu, L., Bovik, A.C.: Foveation Scalable Video Coding with Automatic Fixation Selection. IEEE Trans. Image Processing 12(2), 243–254 (2003)
Basu, A., Wiebe, K.: Videoconferencing Using Spatially Varying Sensing with Multiple and Moving Foveas. In: Proc. IEEE Intl. Conference on Pattern Recognition (October 1994)
Kelly, D.H.: Motion and Vision II. Stabilized Spatio-Temporal Threshold Surface. J. Opt. Soc. Amer. 69(10), 1340–1349 (1979)
Pei, S.-C., Lai, C.-L.: Very Low Bit-Rate Coding Algorithm for Stereo Video with Spatiotemporal HVS Model and Binary Correlation Disparity Estimator. IEEE Journal on Selected Areas in Communications 16(1), 98–107 (1998)
Daly, S.: Engineering Observations from Spatiovelocity and Spatiotemporal Visual Models. IS&T/SPIE Conference on Human Vision and Electronic and Electronic Imaging IV 3644, 162–166 (1999)
Yee, H., Pattanaik, S., Greenberg, D.P.: Spatiotemporal Sensitivity and Visual Attention for Efficient Rendering of Dynamic Environments. ACM 2001 Trans. Computer Graphics 20(1), 39–65 (2001)
Tan, S.H., Pang, K.K., Ngan, K.N.: Classified Perceptual Coding with Adaptive Quantization. IEEE Trans. Circuits and Systems for Video Technology 6(4), 375–388 (1996)
Tang, C.-W., Chen, C.-H., Yu, Y.-H., Tsai, C.-J.: Visual Sensitivity Guided Bit Allocation for Video Coding. Accepted by IEEE Trans. Multimedia (2005)
Itti, L.: Quantifying the Contribution of Low-Level Saliency to Human Eye Movements in Dynamic Scenes. Visual Cognition (2005)
Koch, C.: Biological Models of Motion Perception: Spatio-Temporal Energy Models and Electrophysiology (2004)
Ma, Y.-F., Zhang, H.-J.: A Model of Motion Attention for Video Skimming. In: Proc. Int. Conf. Image Processing, vol. 1, pp. I-129–I-132 (2002)
Chitprasert, B., Rao, K.R.: Human Visual Weighted Progressive Image Transmission. IEEE Trans. Communication 38, 1040–1944 (1990)
Watson, A.B.: Visual Optimization of DCT Quantization Matrices for Individual Images. In: Proc. AIAA Computing in Aerospace 9, pp. 286–291. American Institute of Aeronautics and Astronautics, San Diego (1993)
Pereira, F., Ebrahimi, T.: The MPEG-4 Book, pp. 669–675 (2002)
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tang, CW. (2005). Motion Perception Based Adaptive Quantization for Video Coding. In: Ho, YS., Kim, H.J. (eds) Advances in Multimedia Information Processing - PCM 2005. PCM 2005. Lecture Notes in Computer Science, vol 3767. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581772_12
Download citation
DOI: https://doi.org/10.1007/11581772_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30027-4
Online ISBN: 978-3-540-32130-9
eBook Packages: Computer ScienceComputer Science (R0)