Jung-Hak Nam

Pixel-Wise Unified Rate-Quantization Model for Multi-Level Rate Control

In this paper, we present a pixel-wise unified rate quantization (R-Q) model for a low-complexity rate control on configurable coding units of high efficiency video coding (HEVC). In the case of HEVC, which employs hierarchical coding block structure, multiple R-Q models can be employed for the various block sizes. However, we found that the ratios of distortions over bits for all the blocks are a nearly constant because of employment of the rate distortion optimization technique. Hence, one relationship model between rate and quantization can be derived from the characteristic of similar ratios of distortions over bits regardless of block sizes. Thus, we propose the pixel-wise unified R-Q model for HEVC rate control working on the multi-level for all block sizes. We employ a simple leaky bucket model for bit control. The rate control based on the proposed pixel-wise unified R-Q model is implemented on HEVC test model 6.1 (HM6.1). According to the evaluation for the proposed rate control, the average matching percentage to target bitrates is 99.47% and the average PSNR degradation is 0.76 dB. Based on the comparative study, we found that the proposed rate control shows low bit fluctuation and good RD performance, compared to R-lambda rate control for long sequences.

Scalable video coding based on high efficiency video coding (HEVC)

In this paper, we propose two structures for scalable video coding (SVC) based on HEVC. Several inter-layer prediction mechanisms are introduced to improve coding efficiency of the proposed HEVC-based SVC. The proposed inter-layer predictions are developed on single-loop and multi-loop decoding structures. We found that the proposed SVC is able to decrease average bitrates of enhancement layers by about 10.2% for the all-intra case, and 7.4% for the random access case, compared with single layer coding with no inter-layer prediction in multi-loop decoding. In addition, the single-loop decoding with the proposed inter-layer predictions achieves coding gains of 10.2% for the all-intra case, and 2.6% for the random access case.

HEVC-based adaptive quantization for screen content videos

In general, quality of compressed videos for screen contents is not as good as those for natural videos with the conventional video compression standards due to different properties of textures. In this paper, we present an adaptive quantization method on high efficiency video codec (HEVC) in order to improve coding gain for screen contents. The proposed method adaptively enables quantization either in the spatial domain or in the transform domain. The quantization in the spatial domain is directly conducted for residual signals without any transformations. For the areas for spatial quantization, bilateral filter is used to keep edge and not to generate artifact across boundaries. Experimental results show that the proposed method achieves coding gains of 3.6%, 4.0%, and 4.7% in BD-bitrate for random access, all-intra, and low-delay modes with the high efficiency configuration, respectively.

Lossless video coding based on pixel-wise prediction

The state-of-the-art H.264/AVC was designed for lossy video coding in the beginning. Recently, the H.264/AVC FRExt was developed by removing transformation and quantization for lossless coding. In this paper, we propose an efficient intra lossless coding method based on a pixel-wise prediction. The proposed algorithm introduces an additional intra prediction mode that employs the LOCO-I predictor of JPEG LS. We found that the proposed lossless coding algorithm achieved approximately 22.0, 2.6, and 10.7% bit saving in terms of compression ratio, compared to the H.264/AVC FRExt, lossless intra 4:4:4, and Takamura’s lossless coding methods, respectively.

Sample Adaptive Offset Parallelism in HEVC

We propose a parallelization method for SAO, in-loop filter of HEVC. SAO filtering proceeds along CTB lines and there exists data dependency between inside and outside of CTB boundaries. Data dependency makes data-level parallelization hard. In this paper, we equally divided an entire frame into sub regions. With a little amount of memory, proposed method shows 1.9 times of performance enhancement in terms of processing time.

Parallel Method for HEVC Deblocking Filter based on Coding Unit Depth Information

In this paper, we propose a parallel deblocking algorithm to resolve workload imbalance when the deblocking filter of high efficiency video coding (HEVC) decoder is parallelized. In HEVC, the deblocking filter which is one of the in-loop filters conducts two-step filtering on vertical edges first and horizontal edges later. The deblocking filtering can be conducted with high-speed through data-level parallelism because there is no dependency between adjacent edges for deblocking filtering processes. However, workloads would be imbalanced among regions even though the same amount of data for each region is allocated, which causes performance loss of decoder parallelization. In this paper, we solve the problem for workload imbalance by predicting the complexity of deblocking filtering with coding unit (CU) depth information at a coding tree block (CTB) and by allocating the same amount of workload to each core. Experimental results show that the proposed method achieves average time saving (ATS) by 64.3%, compared to single core-based deblocking filtering and also achieves ATS by 6.7% on average and 13.5% on maximum, compared to the conventional uniform data-level parallelism.

Scalable Multi-view Video Coding based on HEVC

In this paper, we propose an integrated spatial and view scalable video codec based on high efficiency video coding (HEVC). The proposed video codec is developed based on similarity and uniqueness between the scalable extension and 3D multi-view extension of HEVC. To improve compression efficiency using the proposed scalable multi-view video codec, inter-layer and interview predictions are jointly employed by using high-level syntaxes that are defined to identify view and layer information. For the inter-view and inter-layer predictions, a decoded picture buffer (DPB) management algorithm is also proposed. The inter-view and inter-layer motion predictions are integrated into a consolidated prediction by harmonizing with the temporal motion prediction of HEVC. We found that the proposed scalable multi-view codec achieves bitrate reduction of 36.1%, 31.6% and 15.8% on the top of ×2, ×1.5 parallel scalable codec and parallel multi-view codec, respectively.

Inter-layer Texture and Syntax Prediction for Scalable Video Coding

In this paper, we demonstrate inter-layer prediction tools for scalable video coders. The proposed scalable coder is designed to support not only spatial, quality and temporal scalabilities, but also view scalability. In addition, we propose quad-tree inter-layer prediction tools to improve coding efficiency at enhancement layers. The proposed inter-layer prediction tools generate texture prediction signal with exploiting texture, syntaxes, and residual information from a reference layer. Furthermore, the tools can be used with inter and intra prediction blocks within a large coding unit. The proposed framework guarantees the rate distortion performance for a base layer because it does not have any compulsion such as constraint intra prediction. According to experiments, the framework supports the spatial scalable functionality with about 18.6%, 18.5% and 25.2% overhead bits against to the single layer coding. The proposed inter-layer prediction tool in multiloop decoding design framework enables to achieve coding gains of 14.0%, 5.1%, and 12.1% in BD-Bitrate at the enhancement layer, compared to a single layer HEVC for all-intra, low-delay, and random access cases, respectively. For the single-loop decoding design, the proposed quad-tree inter-layer prediction can achieve 14.0%, 3.7%, and 9.8% bit saving.

Novel Motion and Disparity Prediction for Multi - view Video Coding

This paper presents an efficient motion and disparity prediction method for multi-view video coding based on the high efficient video coding (HEVC) standard. The proposed method exploits inter-view candidates for effective prediction of the motion or disparity vector to be coded. The inter-view candidates include not only the motion vectors of adjacent views, but also global disparities across views. The motion vectors coded earlier in an adjacent view were found to be helpful in predicting the current motion vector to reduce the number of bits used in the motion vector information. In addition, the proposed disparity prediction using the global disparity method was found to be effective for interview predictions. A multi-view version based on HEVC was used to evaluate the proposed algorithm, and the proposed correspondence prediction method was implemented on a multi-view platform based on HEVC. The proposed algorithm yielded a coding gain of approximately 2.9% in a high efficiency configuration random access mode.

Macroblock-based adaptive loop filter for all intra-coding

Abstract. A macroblock-based adaptive loop filter (MBALF) to improve coding gain for all intra-coding was presented. The proposed method adaptively applies the adaptive loop filter for each reconstructed macroblock (MB) in order to reduce the blocking artifact caused by the quantization process. The MBALF can improve coding efficiency of intra-predicted MBs as it is conducted prior to intra-prediction for the subsequent MBs in a slice. We found that the proposed MBALF yields a coding gain of approximately 7.1% compared to the H.264/AVC High profile. In addition, we achieved a coding gain of approximately 8.9%, on average, by combining the conventional in-loop filter, block-based, adaptive filter control.