Parallel Content-Aware Adaptive Quantization-Oriented Lossy Frame Memory Recompression for HEVC

Since the development of ultrahigh-definition video, the huge bandwidth and power requirements of external memory have hindered the development of video encoder applications. Power constraints have become a particularly serious problem for portable video codec systems. With high-rate configurations [quantization parameter (QP) ≤ 22 in HEVC test model (HM) reference software], the compression performance of the existing lossless compression algorithms noticeably degrades, because the reference frames are becoming rich of textures. On the other hand, the mathematical analysis of this paper revealed that more quantization noises can be endured by the texture-rich area. Therefore, we develop an adaptive quantization-oriented parallel lossy frame memory recompression algorithm. The contributions of this paper include the following. First, a content-aware adaptive quantization method is devised to achieve a stable high compression ratio that does not deteriorate for highly quality texture-rich pictures. When QP$\in $ [12, 22], a data reduction ratio improvement of up to 14% is obtained compared with the best lossless algorithm. Furthermore, it can reduce the quality loss by 0.49-3.36 dB in terms of Bjøntegaard delta peak signal-to-noise rate (BD-PSNR) compared with the fixed length quantization method. Second, to solve the low throughput problem caused by the pixel-grain prediction method, a parallel directional prediction scheme is developed. It can double or quadruple the throughput with a prediction accuracy loss of only 1.7% or 3.3%, respectively. Using the above-mentioned methods, bandwidth and memory requirements are reduced up to 70.6% and 41.0%, respectively, with a corresponding savings of 59.3% in the dynamic power consumption of the off-chip dynamic random access memory, while the BD-PSNR is -0.04 dB, or, equivalently, Bjøntegaard delta bit rate (BD-BR) is 1.27%. Using TSMC 65-nm CMOS technology, the proposed frame memory compressor and decompressor can achieve the throughputs of up to 2.89 and 2.26 Gpixels/s, respectively. It is applicable to a Super Hi-Vision(8K)@68-frames/s real-time encoding with a Level D reference data reuse scheme.