Abstract
Most of the fast search motion estimation algorithms reduce the computational complexity of motion estimation (ME) greatly by checking only a few search points inside the search area. In this paper, we propose a new algorithm—multi-layer motion estimation (MME) which reduces the computational complexity of each distortion measure instead of reducing the number of search points. The conventional fast search motion estimation algorithms perform ME on the reference frame with full distortion measure; on the contrary, the MME performs ME on the layers with partial distortion measures to enhance the computational speed of ME. A layer is an image which is derived from the reference frame; each macro-pixel value in the layer represents the sum of the values of the corresponding pixels in the reference frame. A hierarchical quad-tree structure is employed in this paper to construct multiple layers from the reference frame. Experimental results on different video sequences show evidence that many motion vectors have been found similar both in the reference frame and the layers. The effectiveness of the proposed MME algorithm is compared with that of some state-of-the-art fast block matching algorithms with respect to speed and motion prediction quality. Experimental results on a wide variety of video sequences show that the proposed algorithm outperforms the other popular conventional fast search motion estimation algorithms computationally while maintaining the motion prediction quality very close to the full-search algorithm. Moreover, the proposed algorithm can achieve a maximum of 97.99 % speed-improvement rate against the fast full-search motion estimation algorithms which are based on hierarchical block matching process. The proposed MME performs the motion estimation on the layers by using three types of search patterns. The derivation of these search patterns exploits the characteristic of the center-biased motion vector distribution and that of less intensive block distortion measurement of the layers.










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Babionitakis, K., Doumenis, G., Georgakarakos, G., Lentaris, G., Nakos, K., Reisis, D., Sifnaios, I., Vlassopoulos, N.: A real-time motion estimation FPGA architecture. J. Real Time Image Process. 3(1–2), 3–20 (2008)
Nuñez-Yañez, L.J., Nabina, A., Hung, E., Vafiadis, G.: Cogeneration of fast motion estimation processors and algorithms for advanced video coding. Very Larg. Scale Integr. VLSI Syst. IEEE Trans. 20(3), 437–448 (2012)
Monteiro, E., Maule, M., Sampaio, F., Diniz, C., Zatt, B., Bampi, S.: Real-time block matching motion estimation onto GPGPU. In image processing (ICIP), 2012 19th IEEE International Conference on, pp. 1693–1696 (2012)
Hui, J., Liming, W.: Research on embedded vehicle image monitoring algorithms based on DSP. World Automation Congress (WAC), 2012, vol., no. 1, 3, pp. 24–28 (2012)
Zhang, J., Nezan, J.-F., Cousin, J.-G.: Implementation of motion estimation based on heterogeneous parallel computing system with open CL. In High Performance Computing and Communication 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), 2012 IEEE 14th International Conference on, pp. 41–45 (2012)
González, D., Botella, G., García, C., Prieto, M., Tirado, F.: Acceleration of block-matching algorithms using a custom instruction-based paradigm on a Nios II microprocessor. EURASIP J. Adv. Signal Process. 2013, 118 (2013). doi:10.1186/1687-6180-2013-118
Gonzalez, D., Botella, G., Meyer-Baese, U., Garcia, C., Sanz, C., Prieto-Matías, M., Tirado, F.: A low cost matching motion estimation sensor based on the NIOS II Microprocessor. Sens Basel 12, 13126–13149 (2012). doi:10.3390/s121013126
Li, W., Salari, E.: Successive elimination algorithm for motion estimation. IEEE Trans. Image Process. 4, 105–107 (1995)
Lee, C., Chen, L.: A fast motion estimation algorithm based on the block sum pyramid. IEEE Trans. Image Process. 6(11), 1587–1591 (1997)
Gao, X.Q., Duanmu, C.J., Zou, C.R.: A multilevel successive elimination algorithm for block matching motion estimation. IEEE Trans. Image Process. 9, 501–504 (2000)
Zhu, C., Qi, W.S., Ser, W.: Predictive fine granularity successive elimination for fast optimal block matching motion estimation. IEEE Trans. Image Process. 14(2), 213–221 (2005)
Liu, Shao-Wei, Wei, Shou-Der, Lai, Shang-Hong: Fast optimal motion estimation based on gradient-based adaptive multilevel successive elimination. IEEE Trans. Circuits Syst. Video Technol. 18(2), 156–160 (2008)
Jung, J.-H., Lee, H.-S., Lee, J.H., Park, D.-J.: A novel template matching scheme for fast full-search boosted by an integral image. IEEE Signal Process. Lett. 17(1), 107–110 (2010)
Koga, T., Iinuma, K., Hirano, A., Iijima, Y., Ishiguro, T.: Motion compensated interframe coding for video conferencing, in Proc. Nat. Telecommun. Conf., New Orleans, LA, pp. G5.3.1–G5.3.5 (1981)
Li, R., Zeng, B., Lio, M.L.: A new three-step search algorithm for block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 4(4), 438–442 (1994)
Zhu, S., Ma, K.K.: A new diamond search algorithm for fast block matching motion estimation. IEEE Trans. Image Process. 9(2), 287–290 (2000)
Tham, J.Y., Ranganath, S., Ranganath, M., Kassim, A.A.: A novel unrestricted center-biased diamond search algorithm for block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 8, 369–377 (1998)
Nie, Y., Ma, K.K.: Adaptive rood pattern search for fast block matching motion estimation. IEEE Trans. Image Process. 11(12), 1442–1449 (2002)
Ma, K.K., Qiu, G.: An improved adaptive rood pattern search for fast block-matching motion estimation in JVT/H.26 l. Proc. IEEE Int. Symp. Circuits Syst. (ISCAS) 2, 25–28 (2003)
Zhu, C., Lin, X., Chau, L.-P.: Hexagon-based search pattern for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 12(5), 349–355 (2002)
Zhu, C., Lin, X., Chau, L.P., Po, L.M.: Enhanced hexagonal search for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 14(10), 1210–1214 (2004)
Po, L.M., Ting, C.W., Wong, K.M., Ng, K.H.: Novel point oriented inner searches for fast block motion estimation. IEEE Trans. Multimed 9(1), 9–15 (2007)
Zou, B.-J., Shi, C., Xu, C.-H., Chen, S.: Enhanced hexagonal-based search using direction-oriented inner search for motion estimation. IEEE Trans. Circuits Syst. Video Technol. 20(1), 156–160 (2010)
Cheung, C.-H., Po, L.-M.: A novel cross-diamond search algorithm for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 12(12), 1168–1177 (2002)
Cheung, C.-H., Po, L.-M.: Novel cross-diamond-hexagonal search algorithms for fast block motion estimation. IEEE Trans. Multimed. 7(1), 16–22 (2005)
Tourapis, A. M.: Enhanced predictive zonal search for single and multiple frame motion estimation. Proc. SPIE Visual Commun. Image Process., San Jose, CA, pp. 1069–1079 (2002)
Kuo, C.-M., Kuan, Y.-H., Hsieh, C.-H., Lee, Y.-H.: A novel prediction-based directional asymmetric search algorithm for fast block-matching motion estimation. IEEE Trans. Circuits Syst. Video Technol. 19(6), 893–899 (2009)
Chen, Z., Xu, J., He, Y., Zheng, J.: Fastinteger-pel and fractionalpelmotion estimation for H.264/AVC. J. Vis. Commun. Image Represent 17(2), 264–290 (2006)
Po, L.-M., Ng, K.-H., Cheung, K.-W., Wong, K.-M., Uddin, Y.M.S., Ting, C.-W.: Novel directional gradient descent searches for fast block motion estimation. IEEE Trans. Circuits Syst. Video Technol. 19(8), 1189–1195 (2009)
Ndili, O., Ogunfunmi, T.: Algorithm and architecture co-design of hardware-oriented, modified diamond search for fast motion estimation in H.264/AVC. IEEE Trans. Circuits Syst. Video Technol. 21(9), 1214–1227 (2011)
Paramkusam, A.V., Reddy, V.S.K.: The efficient optimal and suboptimal motion estimation algorithms. Signal Image Video Process. (2013). doi:10.1007/s11760-013-0562-y
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Paramkusam, A.V., Reddy, V.S.K. An efficient multi-layer reference frame motion estimation for video coding. J Real-Time Image Proc 11, 645–661 (2016). https://doi.org/10.1007/s11554-014-0431-0
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DOI: https://doi.org/10.1007/s11554-014-0431-0