How to acquire accurate and reliable motion parameters from an image sequence is a knotty problem for many applications in image processing, image recognition, and video coding, especially when scenes involve moving objects with various shapes and sizes as well as very fast and complicated motion. In this paper, an improved pel-based motion estimation (ME) algorithm with smoothness constraints is presented, which is based on the investigation and the comparison of different existing pel-based ME (or optical flow) algorithms. Then, in order to cope with various moving objects and their complex motion, a hierarchical ME algorithm with smoothness constraints and postprocessing is proposed. The experimental results show that the motion parameters obtained by the hierarchical ME algorithm are quite creditable and seem to be close to the real physical motion fields if the luminance intensity changes are due to the motion of objects. The hierarchical ME algorithm still provides approximate and smooth vector fields even for scenes that involve some motion-irrelevant intensity changes or blurring caused by violent motion.