This paper describes recent large-scale-integration programmable processors designed for multimedia processing such as real-time compression and decompression of audio and video as well as the generation of computer graphics. As the target of these processors is to handle audio and video in real time, the processing capability must be increased tenfold compared to that of conventional microprocessors, which were designed to handle mainly texts, figures, tables, and photographs. To clarify the advantages of a high-speed multimedia processing capability, we define these chips as multimedia processors. Recent general-purpose microprocessors for workstations and personal computers (PC's) use special built-in hardware for multimedia processing, so the multimedia processors described in this paper include these modified general-purpose microprocessors. After briefly reviewing the history of programmable processors, we classify multimedia processors into five categories depending on their basic architecture. The categories are reduced instruction set computer (RISC) microprocessors for workstations, complex instruction set computer microprocessors for PC's, embedded RISC's, low-power digital signal processors (DSP's), which are mainly used for mobile communications devices, and media processors that support PC's for multimedia applications. These five classes are then grouped into two: microprocessors with a multimedia instruction set and highly parallel DSP's. An architectural comparison between these two groups on the basis of Moving Picture Experts Group decoding applications is made, and the advantages and disadvantages of each class are clarified. Future processors, including "system on a chip," and their applications are also discussed.
This paper presents a fast and accurate motion estimation algorithm. To obtain accurate motion vectors while minimizing computational complexity, we adjust the search range for each frame and each block to suit the motion level of the video. An appropriate search range for each frame is determined on the basis of motion vectors and prediction errors obtained for the previous frame. At each block, the search range is determined on the basis of the search range of its frame and of the motion vector values of all adjacent blocks for which those values have already been obtained. With our algorithm, since narrow search ranges are chosen for areas in which little motion occurs, computational complexity can be reduced without degrading estimation accuracy. Since wide search ranges are chosen for areas of significant motion, good video-quality encoding can be maintained. In the encoding of an SDTV size video, the addition of range adjustment results in a reduction in the computational complexity of motion estimation of roughly 65%, while maintaining the same video quality.
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