Low-complexity block-based motion estimation algorithm using adaptive search range adjustment

Abstract

We propose an adaptive search range adjustment algorithm that is particularly suitable for low-bit-depth motion estimation approaches. Typical low-bit-depth motion estimation approaches, such as one-bit transform (1BT), two-bit transform (2BT), and truncated gray-coded bit-plane matching (TGCBM), perform a full search with low-bit expression. We propose combining a search-range adjustment, which can be predicted by using motion vector information of the reference frame and the existing bit-wise matching methods, such as 1BT, 2BT, and TGCBM. Combining this proposed algorithm and low-bit expression enhances both motion estimation accuracy and time consumption. Experimental results show that low-bit-depth motion estimation approaches using this proposed algorithm have an outstanding performance compared with those without the proposed algorithm both in motion estimation accuracy and time consumption.