Zhengyi Luo

H.264/Advanced Video Control Perceptual Optimization Coding Based on JND-Directed Coefficient Suppression

The field of video coding has been exploring the compact representation of video data, where perceptual redundancies in addition to signal redundancies are removed for higher compression. Many research efforts have been dedicated to modeling the human visual systems characteristics. The resulting models have been integrated into video coding frameworks in different ways. Among them, coding enhancements with the just noticeable distortion (JND) model have drawn much attention in recent years due to its significant gains. A common application of the JND model is the adjustment of quantization by a multiplying factor corresponding to the JND threshold. In this paper, we propose an alternative perceptual video coding method to improve upon the current H.264/advanced video control (AVC) framework based on an independent JND-directed suppression tool. This new tool is capable of finely tuning the quantization using a JND-normalized error model. To make full use of this new rate distortion adjustment component the Lagrange multiplier for rate distortion optimization is derived in terms of the equivalent distortion. Because the H.264/AVC integer discrete cosine transform (DCT) is different from classic DCT, on which state-of-the-art JND models are computed, we analytically derive a JND mapping formula between the integer DCT domain and the classic DCT domain which permits us to reuse the JND models in a more natural way. In addition, the JND threshold can be refined by adopting a saliency algorithm in the coding framework and we reduce the complexity of the JND computation by reusing the motion estimation of the encoder. Another benefit of the proposed scheme is that it remains fully compliant with the existing H.264/AVC standard. Subjective experimental results show that significant bit saving can be obtained using our method while maintaining a similar visual quality to the traditional H.264/AVC coded video.

Raptor Codes Based Unequal Protection for Compressed Video According to Packet Priority

Raptor codes are state-of-the-art forward error correction (FEC) solutions for multimedia transmission, which have been applied to unequal error protection (UEP) of multi-layered media such as scalable video coding. In this paper, we address the problem of UEP for single-layered video over packet erasure channels. By exploiting the different priorities of video packets inside a group of pictures (GOP) and making full use of the good characteristics of standardized Raptor codes at large block length, we propose an optimized UEP framework for single-layered video and develop an efficient algorithm to solve it. Simulation results show that significant gains can be obtained by our method in case of packet losses.

Improving Lossless Intra Coding of H.264/AVC by Pixel-Wise Spatial Interleave Prediction

H.264/AVC adopts many directional spatial prediction models in block-based manner that neighboring pixels on the left and top sides yield prediction for the pixels in a data block to be encoded. However, such models may adapt poorly to the rich textures inside blocks of video signal. In this letter, a new lossless intra coding method based on pixel-wise interleave prediction is presented to enhance the compression performance of H.264/AVC. In our scheme, pixels are coded alternately with interleave prediction, which makes full use of reconstructed pixels to predict later ones in bidirectional or multidirectional manner. Extensive experiments demonstrate that compared to the H.264/AVC standard, our scheme has higher compression ratio, especially for sequences of high resolution. In addition, the scheme can be regarded as a frame-level coding mode and can be easily integrated into the H.264/AVC framework.

Improved error concealment of region of interest based on the H.264/AVC standard

Video transmission over error-prone channels often suffers from inevitable transmission errors, which necessitates proper error concealment (EC) for acceptable image quality. Furthermore, the region of interest (ROI) in images usually draws much attention, and so the EC of the ROI receives special treatment during encoding and decoding. We explore a data hiding-based scheme to effectively improve the EC of the ROI in the case of erasures of large continuous regions, which becomes impractical for conventional EC methods. At the encoder side, motion vectors of the ROI are adaptively embedded in the background based on original quantized coefficients of background macroblocks. Considering the limited embedding capacity of the background, we further propose to assign priorities to each ROI macroblock based on a predefined metric of error propagation. Our scheme is applied with the state-of-the-art H.264/AVC standard in a packet loss scenario, and better video quality can be obtained. Experimental results show that the scheme can improve the EC of the ROI significantly without much loss of coding efficiency.

Performance evaluation of H.265/MPEG-HEVC encoders for 4K video sequences

The H.265/MPEG-HEVC is the latest video coding standard, which achieves an increase of about 50% in coding efficiency compared to its predecessor H.264/MPEG-AVC. Ever since H.265/MPEG-HEVC was designed to replace almost all existing H.264/ MPEG-AVC codecs, high-resolution video coding beyond High Definition (4K, 8K, etc.) has drawn more attention. On the other hand, its well known that reference implementation of HEVC codec, HM, acts an important role during standardization, particularly for evaluation of rate distortion performance of different tools. However, HM is far from a practical codec because of very slow coding speed even on modern multi-core computers. Up to now except for HM few comparisons are known about both the coding performance and the coding speed of practical HEVC encoders for high resolution video sequences. To address this issue, this paper conducts a comprehensive evaluation of latest high performance H.265/MPEG-HEVC encoders, including the open source encoder-x265 and the commercial encoder-DivX265, based on default parameters and a new open 4K video database. Furthermore, latest HM and x264 are also included for performance anchors. The experimental results show DivX265 provides average bit-rate savings of 4.79% relative to HM while x265 with default preset achieves an average reduction of 3.21% in terms of BD-BR saving. In addition, different presets of x265 make a good tradeoff between coding speed and R-D performance while DivX265 is almost as fast as x265 ultrafast preset. We believe such evaluation information could provide a more comprehensive picture of state-of-the-art H.265/MPEG-HEVC encoders.

Improving H.264/AVC video coding with adaptive coefficient suppression

Video coding has been widely adopted to achieve pleasant video quality at constrained bitrate. In this paper, adaptive frequency coefficient suppression directed by Human Visual System (HVS) is presented for H.264 video coding. Firstly, starting from Just Noticeable Distortion (JND) models for the classic DCT domain, we deduce a JND threshold for the H.264 transform domain with decent adaptation. Then the resultant threshold is used to adaptively suppress the transform coefficients of prediction residuals. It should be noted that our scheme is fully compatible with the H.264 standard. And experimental results show that compared to normal methods, significant bitrate reduction can be obtained by our scheme at similar subjective quality.

Evaluation of beyond-HEVC entropy coding methods for DCT transform coefficients

Entropy coding, which acts as one of the most important compression tools in video coding standard, had been improved step by step for HEVC. There are also several advanced methods which provide better performance than current solutions of HEVC proposed during the standardization of HEVC. However, these methods are all tested in different conditions. Comprehensive evaluation of these advanced methods under a common scenario is desired to indicate where the potential improvement of entropy coding may come from for next generation video codec. In this paper, we first introduce several advanced entropy coding methods for DCT transform coefficients, which aim to improve CABAC performance from two aspects - context modeling and probability updating. Then some modifications based on these original ones are presented. Comprehensive comparison of these methods is conducted under common test conditions. Besides, some combined methods of these two aspects are also tested. Experimental results show that all individual approaches can achieve coding gain and two new combined methods can reduce the BD-Rate up to 1.7%, 1.2% and 1.0% on common test sequences and 1.4%, 1.0% and 1.1% on 4K sequences under all intra, random access and low delay configurations, respectively.

A novel parallel-friendly rate control scheme for HEVC

Rate control plays a key role in video coding, which has a significant effect on encoder performance. With parallel video coding frameworks more and more popular, rate control suitable for parallel coding is highly desired. However, most rate control algorithms only focus on the rate distortion performance but ignoring the data correlation in parallel coding. In this paper, based on the parallel framework of the x265 encoder, we propose a parallel-friendly rate control scheme for HEVC coding, which supports both frame level and slice level parallel. Experimental results show that the proposed algorithm can achieve not only highly accurate rate control but also excellent rate distortion performance under parallel coding.

Temporal dependent bit allocation scheme for rate control in HEVC

In this paper, we propose a temporal dependent bit allocation scheme for rate control in state-of-the-art High Efficiency Video Coding (HEVC) standard, to improve its coding performance by utilizing the temporal correlation information. In typical rate control scheme, the bit is allocated to different Coding Tree Units (CTUs) according to their complexity, which reflect their texture and motion information in some degree. However, this scheme ignores the temporal correlation between different frames, which leads to the bit allocation is not the optimal for the whole sequence. Therefore, we refine the bit allocation by taking into account temporal information, especially different coding units distortion influence on the future frames. The result shows that under the same rate control performance, proposed scheme can effectively improve the coding quality performance, especially the Structure Similarity (SSIM) quality performance, the subjective assesment also shows very well.

Offset based leaky prediction for error resilient ROI coding

During the period of transmission, video data usually suffer from transmission errors inevitably. Intra update is a common approach to stop error propagation. However, damaged images cannot recover until next update in case of errors, which often leads to annoying effect. In this paper, we propose an enhanced leaky prediction approach that enables the Region-Of-Interest (ROI) of images to recover gently from the immediate succeeding frame of erroneous ones in favor of better human perception. Moreover, an optimized offset compensation technique is designed to improve coding performance. Experimental results show that the proposed scheme can achieve better image quality for ROI and the fluctuation of bitrate is greatly reduced, compared to the intra update method.