In the rate-distortion optimization (RDO), the process of choosing the best prediction mode is performed through exhaustive executions of the whole encoding process, increasing significantly the encoder computational complexity. Considering H.264/AVC intra frame prediction, there are several modes to encode a macroblock (MB). This work proposes an algorithm and the hardware design for a fast intra frame mode decision module for H.264/AVC encoders. The application of the proposed algorithm reduces in more than 10 times the number of encoding iterations for choosing the best intramode when compared with RDO-based decision. The architecture was synthesized to FPGA and achieved an operation frequency of 98？MHz processing more than 300？HD1080p frames per second. With this approach, we achieved one order-of-magnitude performance improvement compared with RDO-based approaches, which is very important not only from the performance but also from the energy consumption perspective for battery-operated devices. In order to compare the architecture with previously published works, we also synthesized it to standard cells. Compared with the best previous results reported, the implemented architecture achieves a complexity reduction of five times, a processing capability increase of 14 times, and a reduction in the number of clock cycles per MB of 11 times. 1. Introduction H.264/AVC is the state-of-art video compression standard proposed by ITU-T and ISO-IEC [1]. It has shown significantly better coding performance than existing video coding standards, for example, about 50% bit-rate reduction compared with MPEG-2, and, for this reason, it has been adopted by most of electronic devices that encode digital video, such as camcorders and mobile phones. A huge amount of coding options have been included in the H.264/AVC encoder to achieve a better coding efficiency for different video sequences. Since all video codecs, as well as H.264/AVC, include lossy compression schemes, the video encoder must know how much the video quality is degraded for a given target quality, that is, there is a direct relation between the amount of bits of the coded video and its visual quality. Figure 1 shows how the video quality behaves for a target bit-rate of a coded video. The video quality is measured in peak signal-to-noise ratio (PSNR), and the bit-rate is measured in bits per second (bps). The point a in Figure 1 shows a very low bit-rate video with very degraded quality, which is not desirable for most applications. The point c in Figure 1 shows a higher quality video but with very
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