This paper presents a new motion estimation algorithm, called the adaptive motion estimation (AME). The AME algorithm exploits the information gathered from the previous frame to derive a parameter, called CF (correlation parameter), and employs CF to classify the blocks in the current frame into potentially dependent blocks and potentially independent blocks. AME applies different motion estimation methods for potentially dependent blocks and potentially independent blocks to achieve better estimation accuracy and lower computational complexity. Simulation results showed that the proposed AME algorithm has both lower computational complexity and higher PSNR than other motion estimation algorithms, such as three-step search (TSS), new three-step search (NTSS), four-step search (4SS), and the NPSA (new predictive search area) algorithm.

This paper introduces a novel superscalar micro-architecture, called IAS-S, and its related software techniques. We treat two basic problems in superscalar machines. First, we seek a feasible hardware platform which allows the compiler to perform more aggressive instruction scheduling. Second, we develop a good way of communication between the instruction scheduler and register allocator to avoid inadequate register allocation resulting in poor instruction schedules. For the first part, IAS-S employs the Conjugate Register File (CRF) scheme to support multilevel instruction boosting so that a greater amount of instruction-level parallelism in a program can be identified at compile time. For the second part, the instruction scheduling in the IAS-S compiler consists of two passes, prepass and postpass, and a scheduling-conflict graph is built for the register allocator during the prepass scheduling. In this manner, the register allocator can take the potential benefit for later postpass instruction scheduling into account and thus prevents inadequate register allocation.

This article is concerned with creating more realistic images of 3D scenes which are moving relative to the viewer at such high speeds that the propagation delay of light signals and other relativistic effects can not be neglected. Creating images of 3D scenes in relativistic motion might have important applications to science-fiction films, computer games, and virtual environments. We shall discuss the following problems: (1) how to determine the visual appearance of a rapidly moving object, (2) how to determine the apparent radiance of a scene point on a moving object, (3) how to determine the incident irradiance at a scene point coming from a moving light source, (4) how to determine the color of a rapidly moving object, and (5) how to generate shadows when there are relative motions between the viewer, the scenes, and the light sources. Detailed examples are also given to show the result of shading with the relativistic effects taken into account.

IAS-S Supports boosting with “semantic register” and boosting boundary register to remove the dependences caused by conditional branches. In IAS-S, there is no dedicated shadow register file, and multiple levels of boosting is supported without multiple copies of register files. Any general-purpose register in IAS-S can be regarded as a sequential register or a shadow register flexibly. Furthermore, multi-way jump mechanism is combined with boosting to reduce the penalty due to frequent control transfers.