In this paper, we compare the video codecs AV1 (version 1.0.0-2242 from August 2019), HEVC (HM and x265), AVC (x264), the exploration software JEM which is based on HEVC, and the VVC (successor of HEVC) test model VTM (version 4.0 from February 2019) under two fair and balanced configurations: All Intra for the assessment of intra coding and Maximum Coding Efficiency with all codecs being tuned for their best coding efficiency settings. VTM achieves the highest coding efficiency in both configurations, followed by JEM and AV1. The worst coding efficiency is achieved by x264 and x265, even in the placebo preset for highest coding efficiency. AV1 gained a lot in terms of coding efficiency compared to previous versions and now outperforms HM by 24% BD-Rate gains. VTM gains 5% over AV1 in terms of BD-Rates. By reporting separate numbers for JVET and AOM test sequences, it is ensured that no bias in the test sequences exists. When comparing only intra coding tools, it is observed that the complexity increases exponentially for linearly increasing coding efficiency.
In video coding standards like H.264 / MPEG-4 AVC, the encoder performs motion estimation in order to utilise temporal dependencies within a sequence. In addition to the rate of the residue, the encoder has to allocate bits for motion vectors required to compensate the motion at the decoder. This bit rate increases for smaller block sizes, since more motion vectors need to be transmitted. Therefore, motion compensation using dense motion vector field is not feasible for such an architecture.This paper proposes to estimate motion for coding of B frames at the decoder. Using this decoder-side motion estimation, the transmission of the motion vectors is not necessary and the bit rate is reduced. Furthermore, prediction quality is higher in many cases resulting in a coding gain of up to 1.7 dB at low bit rates and 0.2 dB at higher bit rates.
Mesh-based piecewise planar motion compensation and optical flow clustering for ROI codingholger meuel, marco munderloh, matthias reso and jörn ostermann For the transmission of aerial surveillance videos taken from unmanned aerial vehicles (UAVs), region of interest (ROI)-based coding systems are of growing interest in order to cope with the limited channel capacities available. We present a fully automatic detection and coding system which is capable of transmitting high-resolution aerial surveillance videos at very low bit rates. Our coding system is based on the transmission of ROI areas only. We assume two different kinds of ROIs: in order to limit the transmission bit rate while simultaneously retaining a high-quality view of the ground, we only transmit new emerging areas (ROI-NA) for each frame instead of the entire frame. At the decoder side, the surface of the earth is reconstructed from transmitted ROI-NA by means of global motion compensation (GMC) . In order to retain the movement of moving objects not conforming with the motion of the ground (like moving cars and their previously occluded ground), we additionally consider regions containing such objects as interesting (ROI-MO). Finally, both ROIs are used as input to an externally controlled video encoder. While we use GMC for the reconstruction of the ground from ROI-NA, we use meshed-based motion compensation in order to generate the pelwise difference in the luminance channel (difference image) between the mesh-based motion compensated and the current input image to detect the ROI-MO. High spots of energy within this difference image are used as seeds to select corresponding superpixels from an independent (temporally consistent) superpixel segmentation of the input image inorder to obtain accurate shape information of ROI-MO. For a false positive detection rate (regions falsely classified as containing local motion) of less than 2 we detect more than 97 true positives (correctly detected ROI-MOs) in challenging scenarios. Furthermore, we propose to use a modified high-efficiency video coding (HEVC) video encoder. Retaining full HDTV video resolution at 30 fps and subjectively high quality we achieve bit rates of about 0.6-0.9 Mbit/s, which is a bit rate saving of about 90 compared to an unmodified HEVC encoder.
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