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Abstract. This paper proposes new core-based architectures for motion estimation that are customisable for different coding parameters and hardware resources. These new cores are derived from an efficient and fully parameterisable 2-D single array systolic structure for full-search block-matching motion estimation and inherit its configurability properties in what concerns the macroblock dimension, the search area and parallelism level. The proposed architectures require significantly fewer hardware resources, by reducing the spatial and pixel resolutions rather than restricting the set of considered candidate motion vectors. Low-cost and low-power regular architectures suitable for field programmable logic implementation are obtained without compromising the quality of the coded video sequences. Experimental results show that despite the significant complexity level presented by motion estimation processors, it is still possible to implement fast and low-cost versions of the original core-based architecture using general purpose FPGA devices.

With the recent proliferation of multimedia applications, several fast block matching motion estimation algorithms have been proposed in order to minimize the processing time in video coding. While some of these algorithms adopt pre-defined search patterns that directly reflect the most probable motion structures, other dataadaptive approaches dynamically configure the search pattern to avoid unnecessary computations and memory accesses. Either of these approaches leads to rather difficult hardware implementations, due to their configurability and adaptive nature. As a consequence, two different but quite configurable architectures are proposed in this paper. While the first architecture reflects an innovative mechanism to implement motion estimation processors that support fast but regular search algorithms, the second architecture makes use of an application specific instruction set processor (ASIP) platform, capable of implementing most data-adaptive algorithms that have been proposed in the last few years. Despite their different natures, these two architectures provide highly configurable hardware platforms for real-time motion estimation. By considering a wide set of fast and adaptive algorithms, the efficiency of these two architectures was compared and several motion estimators were synthesized in a Virtex-II Pro XC2VP30 FPGA from Xilinx, integrated within a ML310 development platform. Experimental results show that the proposed architectures can be easily reconfigured in runtime to implement a wide set of real-time motion estimation algorithms.

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Motion estimation is the most demanding operation of a video encoder, corresponding to at least 80% of the overall computational cost. With the proliferation of portable handheld devices that support digital video coding, dataadaptive motion estimation algorithms have been required to dynamically configure the search pattern not only to avoid unnecessary computations and memory accesses but also to save energy. This paper proposes an Application Specific Instruction Set Processor (ASIP) to implement data-adaptive motion estimation algorithms, that is characterized by a specialized data-path and minimum and optimized instruction set. Due to its low-power nature, this architecture is specially adequate to develop motion estimators for portable, mobile and battery supplied devices. A cycle-based accurate simulator was also developed for the proposed ASIP and fast and data-adaptive search algorithms have been implemented, namely, the four-step search and the motion vector field adaptive search algorithms. Based on the proposed ASIP and the considered adaptive algorithms, several motion estimators were synthesized in 0 .13 μm CMOS technology. Experimental results show that very-low power adaptive motion estimators have been achieved to encode QCIF video sequences.