Advanced one-bit transform algorithm with edge enhancement and representative feature extraction for low-complexity and accurate motion estimation
Motion estimation is an essential procedure in video coding and object tracing, but it always has a high computational load. Some low bit-depth motion estimation methods, such as one/two-bit transform or gray coding based methods, have lower complexity. However, one-bit transform based methods are sensitive to noise, whereas two-bit transform and gray coding methods use many bit planes or operations to perform motion estimation. In this paper, we select features with high representative by two means. First, we present an improved one-bit transform with pre-processing techniques. Second, an adaptive matching criterion was introduced to pick out features with higher representative. Moreover, a fast search algorithm is also proposed to reduce the searching cost. The experimental results show that the proposed algorithm outperforms other methods both in matching accuracy and in computation efficiency.