Abstract
In recent years, video compression has emerged as an effective technique to reduce spatial and temporal redundancy in video sequence. Temporal redundancy reduction deals with motion estimation (ME) and motion compensation (MC) algorithm with the matching technique to produce the next encoded video frame with motion vector. Motion estimation is the process of determining the movement of blocks between adjacent video frames by which image information is assessed for similarities that can be reused in subsequent frames. However, computational complexity and resource sharing of the motion estimation algorithm poses great challenges for real time applications. Fast search algorithms emerged as important search technique to achieve real time tracking results. Among the different motion estimation algorithms block matching is the most common used technique. This paper presents a system-level implementation of a wavelet-based H2D video coding. Three block matching motion estimation algorithms are implemented in order to evaluate the overall system performance. In fact, since the chip design and layout process is time consuming and expensive, it is very important to be able to predict the overall system performance in a high-level implementation before its circuit layout is deployed. The aim is to discuss the impact of different block matching motion estimation algorithms on video coding performance. Because of the complexity of the entire motion estimation system, decision in choosing one algorithm versus the other algorithms is often empirical and crucial.