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Hardware implementation and validation of the fast variable block size motion estimation architecture for HEVC Standard

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Abstract

High-Efficiency Video Coding (HEVC) has become popular according to its excellent coding performance, in particular in the case of high-resolution video applications. However, the significant gain in performance is accompanied by a higher encoding complexity compared to the H.264/AVC standard. The motion estimation (ME) is the most time-consuming part that removes temporal redundancy. To reduce the motion estimation complexity, many fast algorithms have been developed in order to minimize search positions and speed up computation but they do not take into account how they can be effectively implemented by hardware. This paper presents a design for the fast ME algorithm with a variable block size of HEVC standard which is the “TZ search”. The design is described in VHDL language and synthesized to Altera Stratix III FPGA. The hardware architecture throughput reaches a processing rate up to 78 million pixels per second at 100 MHz. For the validation proposed design, an IP core is presented using the embedded video system on a programmable chip (SoPC). Finally, compared to other designs existing in the literature, the proposed architecture shows more efficiency in terms of hardware cost and improved performance. This design can be used in ultra-high-definition real-time TV coding (UHD) applications.

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Acknowledgements

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under grant number RGP2/39/44.

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Correspondence to Hassen Loukil.

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This work was supported by the Deanship of Scientific Research at King Khalid University (Grant numbers RGP2/39/44). The authors have no relevant financial or non-financial interests to disclose.

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Loukil, H., Mayet, A.M. Hardware implementation and validation of the fast variable block size motion estimation architecture for HEVC Standard. Multimed Tools Appl 82, 46331–46349 (2023). https://doi.org/10.1007/s11042-023-15628-y

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  • DOI: https://doi.org/10.1007/s11042-023-15628-y

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