The quaternary tree with nested binary and ternary tree structure is an efficient coding unit (CU) partitioning method adopted in Versatile Video Coding (VVC). Compared with quaternary tree only in HEVC, its flexible block sizes improve the coding performance significantly at the cost of computation load increase due to the recursive and nested searching for the best CU structure. In this paper, an early termination algorithm is proposed to skip unnecessary searches in CU size decision. Based on directional gradients, pre-determine the likelihood of binary partition or ternary partition in horizontal or vertical direction for current block, thus the impertinent partition pattern is skipped. The experimental results show that the proposed method is able to save the encoding time up to 51% with about 1.2% BD-rate degradation compared with VVC software reference VTM5.0.

In the latest video coding standard, namely, high-efficiency video coding (HEVC), intra coding efficiency is significantly improved by a quadtree partition structure and more intra prediction modes. For intra coding, 35 intra modes are employed including 33 angular intra prediction (AIP) modes that are effective for blocks with strong directions, and a planar mode and a dc mode that are used to predict smooth regions. However, intra prediction in HEVC still cannot handle complicated blocks well. To deal with this problem, this paper proposes a hybrid intra prediction method to improve the intra prediction efficiency. The proposed hybrid intra prediction method consists of three parts: adaptive template matching prediction (ATMP) by exploring nonlocal correlation, combined local and nonlocal prediction by exploring both local correlation for AIP and non-local correlation for ATMP, and combined neighboring modes prediction that can generate smooth prediction by exploring more local correlations. Experimental results suggest that the proposed hybrid intra prediction method achieves 2.8% BD-rate reduction on average for luma compared to HEVC reference software HM-14.0 under all intra main configurations. The gain can be up to 6.9%. When integrated into joint exploration model -1.0, the proposed method still can achieve 1.2% BD-rate reduction for luma.

Summary form only given. Traditional intra prediction methods for HEVC rely on using the nearest reference lines for predicting a block, which ignore much richer context between the current block and its neighboring blocks and therefore cause inaccurate prediction especially when weak spatial correlation exists between the current block and the reference lines. To overcome this problem, in this paper, an intra-prediction convolutional neural network (IPCNN) is proposed for intra prediction, which exploits the rich context of the current block and therefore is capable of improving the accuracy of predicting the current block. Meanwhile, the reconstruction of the three nearest blocks can also be refined. To the best of our knowledge, this is the first paper that directly applies CNNs to intra prediction for HEVC. Experimental results validate the effectiveness of applying CNNs to intra prediction and the proposed method can achieve 0.70% bitrate reduction compared to HEVC reference software HM-14.0.

The latest video coding standard High Efficiency Video Coding (HEVC) achieves about a 50% bit-rate reduction compared with H.264/AVC under the same perceptual video quality. For intra coding, a coding unit (CU) is recursively divided into a quadtree-based structure from the largest CU 64 × 64 to the smallest CU 8 × 8. Also, up to 35 intra-prediction modes are allowed. These two techniques improve the intra-coding performance significantly. However, the encoding complexity increases several times compared with H.264/AVC intra coding. In this paper, fast intra-mode decision and CU size decision are proposed to reduce the complexity of HEVC intra coding while maintaining the rate-distortion (RD) performance. For fast intra-mode decision, a gradient-based method is proposed to reduce the candidate modes for rough mode decision and RD optimization. For fast CU size decision, the homogenous CUs are early terminated first. Then two linear support vector machines that employ the depth difference and HAD cost ratio (and RD cost ratio) as features are proposed to perform the decisions of early CU split and early CU termination for the rest of the CUs. Experimental results show that the proposed fast intra-coding algorithm achieves about a 54% encoding time reduction on average with only a 0.7% BD-rate increase for the HEVC reference software HM 14.0 under all-intra configuration.

Transform is used to compact the energy of the blocks into a small number of coefficients and is widely used in recent image/video coding standards. In the latest video coding standard high efficiency video coding (HEVC), a combination of discrete cosine transform (DCT) and discrete sine transform (DST) is adopted to transform the residuals from intra prediction. Since the DCT and DST are the fixed transforms that are derived from the Gauss-Markov model, some of residual blocks may not be compacted well by the DCT/DST. In this paper, we propose a signal dependent transform based on singular value decomposition (SVD) for HEVC intracoding. The proposed transform (SDT-SVD) is derived by performing SVD on the synthetic block and applied to the residual block considering the structural similarity between them. Furthermore, we extend SDT-SVD to template matching prediction (TMP) to further improve the intracoding performance. Experimental results show that the proposed transform on angular intra prediction (AIP) outperforms the latest HEVC reference software with a bit rate reduction of 1.0% on average and it can be up to 2.1%. When the proposed transform is extended to TMP-based intracoding, the overall bit rate reduction is 2.7% on average and can be up to 5.8%.

Intra prediction is an important tool in intra-frame video coding to reduce the spatial redundancy. In current coding standard H.265/high-efficiency video coding (HEVC), a copying-based method based on the boundary (or interpolated boundary) reference pixels is used to predict each pixel in the coding block to remove the spatial redundancy. We find that the conventional copying-based method can be further improved in two cases: 1) the boundary has an inhomogeneous region and 2) the predicted pixel is far away from the boundary that the correlation between the predicted pixel and the reference pixels is relatively weak. This paper performs a theoretical analysis of the optimal weights based on a first-order Gaussian Markov model and the effects when the pixel values deviate from the model and the predicted pixel is far away from the reference pixels. It also proposes a novel intra prediction scheme based on the analysis that smoothing the copying-based prediction can derive a better prediction block. Both the theoretical analysis and the experimental results show the effectiveness of the proposed intra prediction method. An average gain of 2.3% on all intra coding can be achieved with the HEVC reference software.

In the latest HEVC video coding standard, angular intra prediction (AIP) applies 35 modes including 33 angular modes which can handle blocks with direction information well, and other 2 modes (DC and planar) which are used to predict smooth blocks. However, for blocks with complex texture, these modes may not give good predictions. Some complex blocks can be predicted well by template matching prediction (TMP) which was proposed to predict blocks having similar patterns in the coded regions of the same frame without the cost of large overheads. In this paper, a novel hybrid AIP/TMP is proposed to improve the prediction efficiency. Experimental results show that the proposed method can achieve a coding gain of about 2.5% for high resolution sequences on average compared to the AIP in HEVC. The gain can be up to 4.2%.

In real-time screen remoting system, frame rate is one of essential factors that affect user experience. Therefore, how to compress diversity of screen contents fast and efficiently is a key issue. Existing video codecs such as H.264 are always used in such a system for screen compression. However, arbitrary-sized regions with large motion always exist in typical screen content videos, which lead to a lower encoding speed and higher bit-rate, thereby decrease the frame rate. This paper proposes an efficient motion detection algorithm, which is fast and efficient for large motion regions. In specific, a region-based motion detection is used to find motion vectors instead of traditional block based motion estimation. The motion vectors are then utilized by H.264 encoder for normal motion compensated prediction. Experimental results show that the proposed algorithm can reduce both encoding time and bit-rate significantly.

Video plus the corresponding depth maps is now the most popular data format for 3D video coding, as it is convenient to synthesize an arbitrary intermediate virtual view without the need to display the depth map for end users. How to compress the depth map efficiently is one of the key problems in 3DVC. In this paper we propose a new distortion model for depth map coding by considering the view synthesis distortion caused by depth distortion and the disparity rounding problem. Simulation results show that the proposed scheme can achieve 34% bit-rate saving for depth map coding, or 1.28 dB gain in terms of PSNR on average for synthesized virtual views.