Akiyuki Tanizawa

Block Based Extra/Inter-Polating Prediction for Intra Coding

In this paper, we propose an efficient intra coding method. The method involves adding an extra/inter-polating prediction method to the conventional H.264/MPEG-4 AVC (H.264) intra prediction method. The proposal consists of two parts. One is to change the sub-block coding order in macroblock (MB). The bottom-right sub-block in MB is predicted using the reference pels on the upper and left side of the sub-block firstly. After that, the other sub-blocks are predicted using not only the reference pels on the upper and/or left side but also ones on the bottom and/or right side of each sub-block. The other part is to use an intra bidirectional prediction method which can use the interpolation of the prediction from upper/left pels and the prediction from bottom/right pels. Experimental results show that our method improves bit reduction by up to 7.7% at the same PSNR compared to H.264.

In-loop filter using block-based filter control for video coding

In this paper, a method of improving coding efficiency is proposed by using the Wiener filter as an in-loop filter. The Wiener filter can minimize the mean square error between the input image and the decoded image. However, errors of some pixels increase by filtering process. Since the filtered pixels are used for motion-compensated prediction, these errors are propagated to the subsequent images. The proposed method divides the decoded image into some fixed blocks, and decides whether to apply the filter for each block adaptively. As a result, by preventing the increase in errors after the filtering process, the coding efficiency can be improved. Experimental results show that the proposed method achieves bitrate reduction of up to 33.9% in Baseline Profile and up to 33.0 % in High Profile at the same PSNR compared to H.264.

A study on fast rate-distortion optimized coding mode decision for H.264

The H.264 video coding standard can achieve considerably higher coding efficiency than any other existing standards by deciding the best mode among many prediction modes and various sixes of prediction blocks. Although the coding efficiency is improved by using Lagrange optimization for the mode decision, computational complexity increases significantly at the encoder. In this paper, we propose the fast rate-distortion optimization method for the hierarchical and adaptive coding mode decision in order to reduce the number of candidates for the best coding mode.

A highly parallelized H.265/HEVC real-time UHD software encoder

H.265/HEVC standard, promising up to twice the compression efficiency over H.264/AVC standard is suitable for encoding UHD videos and has garnered much attention since its inception. With increasing amount of devices supporting UHD, real-time H.265/HEVC encoder and decoder are needed to complete the UHD media ecosystem. In this paper, we present a highly parallelized HEVC software encoder suitable for broadcasting or network streaming applications. Real-time Main 10 profile encoding of 4K UHD videos at 60fps is achieved through an efficient parallel encoder platform comprising of CPUs interconnected by high speed network. The encoder core is optimized with data parallelism and GPU assisted motion estimation. Utilizing temporal parallelism of GOP and spatial parallelism of picture through slicing to encode, scalability and flexibility are achieved. Results show that our encoder system is about 15794 times faster than HEVC test model HM 11.0 and 13 times faster than ×265, an open source HEVC encoder.

Multi-directional implicit weighted prediction based on image characteristics of reference pictures for inter coding

Weighted prediction (WP) in H.264/MPEG-4 AVC (H.264) is an efficient motion compensation technique to predict illumination variation and consists of two modes: an explicit WP (EWP) and an implicit WP (IWP). Since in IWP, only weighting factors are implicitly derived from reference pictures used for bi-prediction, and the offsets are always set to 0, there are issues in that IWP cannot utilize the optimal WP parameters, and cannot be applied to uni-prediction. In order to overcome these issues, this paper presents a novel decoding process to derive WP parameters implicitly by using the Multi-Directional Implicit Weighted Prediction (MD-IWP) method. WP parameters are derived using the image characteristics of reference pictures. By linearly predicting the image characteristics of the target picture using different reference pictures stored in the decoded picture buffer, WP parameters of uni-prediction can also be derived. This method can achieve 15% to 50% bitrate reduction compared to the conventional IWP method. This gain is almost the same or better than in the case of EWP with the simple 1-pass parameter estimation method.

One-Dimensional Directional Unified Transform for intra coding

In this paper, we present the One-Dimensional Directional Unified Transform (1DDUT) for intra coding. Intra prediction in H.264/AVC has eight different directional prediction modes and a DC prediction mode. Since the statistical characteristics of prediction residuals are different in each prediction mode, coding efficiency can be improved by applying the different optimal transform for each prediction mode. However, in order to avoid the increase of the complexity, unification of the transforms is desired. Therefore we classify the characteristics of the prediction residuals along the vertical or the horizontal direction, where each direction has two classes and their characteristics are similar to each other between directions. It is sufficient to use two kinds of 1-D transforms that are designed based on the unified characteristics. One is the well-known Discrete Cosine Transform, and the other is a predetermined 1-D transform based on the Karhunen-Loeve Transform method. 1DDUT switches DCT and the predetermined 1-D transform according to the intra prediction modes. 1DDUT can achieve 8.71% bitrate reduction on average with negligible complexity increase compared to the DCT-like transform used in H.264/AVC.

Efficient weighted prediction parameter signaling using parameter prediction and direct derivation

Weighted prediction (WP) is an efficient motion compensation technique to predict temporal illumination variation. It has been introduced in H.264/MPEG-4 AVC (Advanced Video Coding, H.264) and consists of two modes: an explicit WP (EWP) and an implicit WP (IWP). Since in EWP, a weighting factor and an offset for each reference picture are explicitly transmitted to the decoder, an overhead of these parameters affects the coding efficiency. Since in H.264-based EWP, these parameters are directly encoded without prediction, it is difficult to apply WP for low bitrate applications. In order to reduce the overhead of them, this paper presents an efficient weighted prediction parameter signaling method towards High Efficiency Video Coding (HEVC) standard by introducing a WP parameter prediction and a direct WP parameter derivation. A weighting factor and an offset are predicted using the characteristics of WP parameters and entropy-coded. Moreover, when there are the same entries in reference pictures for prediction list 0 and 1 in the case of B-slices, a set of WP parameters for prediction list 1 is directly derived from that for prediction list 0. The experimental results show that our method can achieve up to 66% overhead bitrate reduction and up to 7% overall bitrate reduction compared to the conventional H.264-based EWP.