High Efficiency Video Coding Lossless Research Articles

An optimized transform and quantization scheme for HEVC intra lossless coding

AbstractThe lossless coding framework of High Efficiency Video Coding (HEVC) comprises prediction and entropy coding, while omitting the transform process. However, residuals derived from prediction continue to demonstrate significant spatial redundancy, which has the potential to compromise the coding efficiency. This article presents an optimized scheme for HEVC intra lossless coding that integrates transform and quantization. In the proposed scheme, a residual block, generated by HEVC, is partitioned into two components: the coefficient block and the error block. The coefficient block, responsible for lossless coding, is obtained through the adoption of the transform and quantization processes employed in HEVC lossy coding. Subsequently, the error block is derived by predicting the residual block using the generated coefficient block. Both the coefficient block and the error block can be effectively encoded utilizing the existing entropy coding scheme in HEVC lossy coding. Rate‐distortion optimization is employed to determine whether the residual block will be partitioned into two components. The proposed scheme is implemented into the HM 12.1 software. Through the utilization of the discrete cosine transform kernel and the discrete sine transform kernel, with a quantization parameter set to 20, on HEVC standard test sequences and the all intra main configuration file, empirical findings substantiate that the proposed methodology attains an average bit‐rate reduction of 3.31%, with a maximum improvement of 12.29% in comparison to HEVC lossless coding.

Gradient-oriented directional predictor for HEVC planar and angular intra prediction modes to enhance lossless compression

Recent advancements in the capture and display technologies motivated the ITU-T Video Coding Experts Group and ISO/IEC Moving Picture Experts Group to jointly develop the High-Efficiency Video Coding (HEVC), a state-of-the-art video coding standard for efficient compression. The compression applications that essentially require lossless compression scenarios include medical imaging, video analytics, video surveillance, video streaming etc., where the content reconstruction should be flawless. In the proposed work, we present a gradient-oriented directional prediction (GDP) strategy at the pixel level to enhance the compression efficiency of the conventional block-based planar and angular intra prediction in the HEVC lossless mode. The detailed experimental analysis demonstrates that the proposed method outperforms the lossless mode of HEVC anchor in terms of bit-rate savings by 8.29%, 1.65%, 1.94% and 2.21% for Main-AI, LD, LDP and RA configurations respectively, without impairing the computational complexity. The experimental results also illustrates that the proposed predictor performs superior to the existing state-of-the-art techniques in the literature.

Performance enhancement of HEVC lossless mode using sample-based angular and planar predictions

High-efficiency video coding (HEVC) is the state-of-the-art video compression standard designed to handle the storage and transmission requirements of next-generation multimedia services. In the lossless mode HEVC, prevailing sample-based prediction algorithms in the literature have shown better prediction accuracy compared to the conventional block-based prediction within the HEVC anchor. This work proposes a sample-based prediction technique to modify the planar prediction mode of HEVC and a complete sample-based predictive encoder for the lossless mode of HEVC. In this work, we propose gradient adaptive sample-based intraprediction (GASP) as a replacement for the block-based planar prediction in HEVC. To obtain the benefits of sample-based prediction methods in both angular and planar prediction modes, we also propose a combination of ISAP, a sample-based angular prediction in the literature, with the newly proposed GASP (CIG). The experimental results demonstrate the superiority of GASP and CIG over other state-of-the-art sample-based prediction strategies in angular and planar prediction modes.

Improved SAP based on adaptive directional prediction for HEVC lossless intra prediction

In HEVC (High Efficiency Video Coding), linear interpolation of the boundary pixels is used as the predictor and pixels within the same PU (Prediction Unit) are in the same prediction direction. When the PU block is large and in high complexity, the prediction performance would worsen. Although many algorithms use the pixel-based weighted averaging or interpolation operations to perform the prediction which improves the performance of bitrate saving notably, there is still space for further improvement. This paper proposed an improved SAP (Sample-based Angular Prediction) algorithm based on adaptive directional prediction (ADSAP). The innovation of this paper lies in two aspects: it puts forward a new method to estimate the best prediction direction of current pixel and it introduces the concept of “frame-level pretreatment” which could greatly improve the encoding speed. Experimental results show that it could save the output bitrate by about 9.4158% when compared with the HEVC lossless intra prediction algorithm, which is better than other typical algorithms. Besides, the encoding and decoding time are reduced by about 11%. Moreover, when the minimum PU size gets larger, the increase of output bitrate of ADSAP is much less than that of HEVC and the conventional SAP algorithm, which makes the proposed algorithm quite suitable for the compression of high resolution videos.

Highly efficient near lossless video compression using selective intra prediction for HEVC lossless mode

Lossless coding mode of high efficiency video coding (HEVC) relies on efficient intra prediction methods for achieving higher compression. Sample based angular intra prediction (SAP) is a modification proposed for the conventional block-based intra prediction (BP) in the HEVC standard. In this paper a selective intra prediction (SIP) algorithm is proposed for lossless intra mode coding within HEVC, which uses an adaptive switching strategy between the two intra prediction methods, BP and modified SAP (MSAP), on a per pixel basis. MSAP is a modification proposed in this work to improve the prediction accuracy of SAP. The proposed SIP algorithm is a near lossless algorithm that selects the best prediction for each pixel to reduce the residual energy thereby increasing the coding efficiency. To circumvent the huge overhead required for the transmission of the selection from encoder to decoder, SIP adopts piggybacking the selection on the least-significant-bit (LSB) of the transmitted residual for each pixel. The proposed approach removes overhead at the expense of a ±1 reconstruction error for each pixel which is negligible for 8-bit or 10-bit input videos. Experimental results show significant coding gains for the proposed SIP over the HEVC anchor and similar state-of-the-art lossless coding algorithms.

Piecewise DC prediction in HEVC

In this paper, we propose an improved DC prediction method for high-efficiency video coding (HEVC) intra coding. The technique involves the application of pixel-wise predictors rather than block-based predictor in the DC mode. In HEVC, the pixels of neighboring reconstructed blocks are used to support multiple directional spatial prediction modes and reduce spatial redundancy. For lossless coding, pixel-by-pixel differential pulse code modulation (DPCM) is applied to directional predictions. Consequently, residuals are reduced and coding efficiency is improved. Since DC prediction still employs block-based coding, pixel-wise DC prediction is needed for better coding efficiency. When compared to HEVC lossless intra coding, the proposed algorithm reduces the bit rate by 5.95%. Furthermore, with pixel-by-pixel DPCM, the average bit rate reduction is 10.64% when compared to HEVC lossless intra coding.

Efficient residual data coding in CABAC for HEVC lossless video compression

After the development of the next generation video coding standard, referred to as high efficiency video coding (HEVC), the joint collaborative team of the ITU-T video coding experts group and the ISO/IEC moving picture experts group has now also standardized a lossless extension of such a standard. HEVC was originally designed for lossy video compression, thus, not ideal for lossless video compression. In this paper, we propose an efficient residual data coding method for HEVC lossless video compression. Based on the fact that there are statistical differences of residual data between lossy and lossless coding, we improved the HEVC lossless coding using sample-based angular prediction (SAP), modified level binarization, and binarization table selection with the weighted sum of previously encoded level values. Experimental results show that the proposed method provides high compression ratio up to 11.32 and reduces decoding complexity.

HEVC Lossless Coding and Improvements

The lossless coding mode of the High Efficiency Video Coding (HEVC) main profile that bypasses transform, quantization, and in-loop filters is described. Compared to the HEVC nonlossless coding mode with the smallest quantization parameter value (i.e., 0 for 8-b video and -12 for 10-b video), the HEVC lossless coding mode provides perfect fidelity and an average bit-rate reduction of 3.2%-13.2%. It also significantly outperforms the existing lossless compression solutions, such as JPEG2000 and JPEG-LS for images as well as 7-Zip and WinRAR for data archiving. To further improve the coding efficiency of the HEVC lossless mode, a sample-based angular intra prediction (SAP) method is presented. The SAP employs the same prediction mode signaling method and the sample interpolation method as the HEVC block-based angular prediction, but uses adjacent neighbors for better intra prediction accuracy and performs prediction sample by sample. The experimental results reveal that the SAP provides an additional bit-rate reduction of 1.8%-11.8% on top of the HEVC lossless coding mode.