DMPDS: A Fast Motion Estimation Algorithm Targeting High Resolution Videos and Its FPGA Implementation

Abstract

This paper presents a new fast motion estimation (ME) algorithm targeting high resolution digital videos and its efficient hardware architecture design. The new Dynamic Multipoint Diamond Search (DMPDS) algorithm is a fast algorithm which increases the ME quality when compared with other fast ME algorithms. The DMPDS achieves a better digital video quality reducing the occurrence of local minima falls, especially in high definition videos. The quality results show that the DMPDS is able to reach an average PSNR gain of 1.85 dB when compared with the well-known Diamond Search (DS) algorithm. When compared to the optimum results generated by the Full Search (FS) algorithm the DMPDS shows a lose of only 1.03 dB in the PSNR. On the other hand, the DMPDS reached a complexity reduction higher than 45 times when compared to FS. The quality gains related to DS caused an expected increase in the DMPDS complexity which uses 6.4-times more calculations than DS. The DMPDS architecture was designed focused on high performance and low cost, targeting to process Quad Full High Definition (QFHD) videos in real time (30 frames per second). The architecture was described in VHDL and synthesized to Altera Stratix 4 and Xilinx Virtex 5 FPGAs. The synthesis results show that the architecture is able to achieve processing rates higher than 53 QFHD fps, reaching the real-time requirements. The DMPDS architecture achieved the highest processing rate when compared to related works in the literature. This high processing rate was obtained designing an architecture with a high operation frequency and low numbers of cycles necessary to process each block.

Register array‐based sum of absolute difference processor with parallel memory system for fast motion estimation

“…Various architectures use dissimilar width of data bus, hence can read and process distinctive number of pixels. Owing to 128 bit data bus width in [4, 9, 10], they can read 16 keel pixel together from search area while due to 32 and 64 bit data bus, implementations presented in [5, 7], can read 4 and 8 keel pixel together. As per Table 2, all existing architectures are using different schemes for multi‐operand addition and process different numbers of pixels in multiple PEs with or without pipeline for SAD computation.…”

“…As per review of literature, for accessing CMBs, architecture presented in [1, 4, 5, 7, 9, 10] are using single memory system while architecture presented in [6] uses parallel memory system. In [6], just block format is used for reading pixels; however, according to [11, 12], parallel memory system can help in accessing pixels in various formats from arbitrary locations.…”

“…Another variant line diamond parallel search (LDPS) [8] is using small diamond pattern and demonstrates speedup with poor quality. Dynamic multipoint DS [9] algorithm begins the search from four locations in addition to the centre; hence need more parallel PEs to compute the best match. The architecture presented in [1] uses hardware‐efficient double DS (HEDDS) BMA which exhibits less number of iterations and claims faster implementation with retaining the quality of encoding compared with existing algorithms such as HEXBS, PHS, DS, HMDS, LDPS etc.…”

An efficient hardware architecture for inter-prediction in H.264/AVC encoders

“…Step Search (3SS) algorithm [10] or diamond-based search algorithm [11], [12] but they do not support variable blocksizes. Another method is multi-resolution search [13]- [15] which provides low latency for prediction.…”

VLSI Implementation of High Performance Optimized Architecture for Video Coding Standards

“…This results in significant computational complexity and consumes up to 80% of the computing power of the encoder. To reduce the computational complexity, numerous optimized search algorithm are available as follows: Three Step Search (TSS), New Three Step Search (NTSS), Four Step Search (FSS), Block Based Gradient Descent Search (BBGDS), Diamond Search (DS), Hexagon-Based Search (HEXBS), Adaptive Rood Pattern Search (ARPS), Cross Diamond Search (CDS) [3][4][5][6][7][8][9][10][11][12]. The TSS reduces the number of computations by using a coarse-to-fine search strategy.…”