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In this paper, a High Efficiency Video Coding (HEVC)-compliant perceptual video coding (PVC) scheme is introduced based on just-noticeable difference (JND) models in both transform and pixel domains. We adopt an existing pixel-domain JND model for the transform skip mode of HEVC and propose a transform-domain JND model for the transform nonskip modes of HEVC. The proposed transform-domain JND model is designed by considering the spatial JND characteristics such as contrast sensitivity, luminance adaptation, and contrast masking effects as well as by considering the summation effects of variable block-sized transforms in HEVC. A temporal JND model is additionally incorporated into the proposed transform-domain JND model to further reduce perceptual redundancy. To incorporate the transform- and pixel-domain JND models into the encoding process in an HEVC-compliant manner, the transform coefficients and residues are suppressed in harmonization with the transform/quantization process and the quantization-only process of HEVC, respectively. To make the JND-based suppression effective, a distortion compensation factor is also proposed to reflect the perceptual distortion in the rate-distortion optimization-based encoding process. Based on subjective quality assessments of the encoded bit streams of test sequences, the proposed HEVC-compliant PVC scheme yields remarkable bitrate reductions of a maximum 49.10% and an average 16.10% with negligible subjective quality loss, compared with an HEVC reference software HEVC test model (HM 11.0). In addition, the proposed HEVC-compliant PVC scheme increases the encoding complexity of HM 11.0 only by an average of 11.25%. [ABSTRACT FROM AUTHOR]

Recently, a new video coding standard, High Efficiency Video Coding (HEVC), has shown greatly improved coding efficiency by adopting hierarchical structures of coding unit (CU), prediction unit (PU), and transform unit (TU). To best achieve the coding efficiency, the best combinations of CU, PU, and TU must be found in the sense of the minimum rate-distortion (R-D) costs. Owing to this, a large computational complexity occurs. Among these CU, PU, and TU, the determination of CU sizes most significantly affects the R-D performance of HEVC encoders, which causes large computational costs in operation with PU and TU size determinations. In spite of recent works in the complexity reduction of HEVC encoders, most of the research has focused on the complexity reduction with fast CU split in intra slice coding and with early TU split in both intra and inter slice. In this paper, we propose a fast and an efficient CU encoding scheme based on the spatiotemporal encoding parameters of HEVC encoders, which consists of an improved early CU SKIP detection method and a fast CU split decision method. For the current CU block under encoding, the proposed scheme utilizes sample-adaptive-offset parameters as the spatial encoding parameter to estimate the texture complexity that affects the CU partition. In addition, the motion vectors, TU size, and coded block flag information are used as the temporal encoding parameters to estimate the temporal complexity that also affects the CU partition. The proposed scheme effectively utilizes the spatiotemporal encoding parameters that are the byproducts during the encoding process of HEVC without additionally required computation. The proposed novel fast CU encoding scheme significantly reduces the total encoding time with negligible RD-performance loss. The experimental results show that the proposed scheme achieves the total encoding time savings of average 49.6% and 42.7% only with average 1.4% and 1.0% bit-rate losses for various test sequences under random access and low delay B conditions, respectively. The proposed scheme has an advantage on the implementation for parallel processing in pipeline structures of HEVC encoders due to its independency with neighboring CU blocks. [ABSTRACT FROM PUBLISHER]

In this paper, a frame-level rate control scheme is proposed based on texture and nontexture rate models for High Efficiency Video Coding (HEVC). Due to more complicated coding structures and the adoption of new coding tools, the statistical characteristics of transform residues are significantly different depending on the depth levels of coding units (CUs) from which the residues are obtained. A new texture rate model is constructed for the transform residues, which are categorized into three types of CUs: low-, medium- and high-textured CUs. One single Laplacian probability PDF model is used for each residue category to derive a rate-quantization model. Based on the Laplacian PDF, a simplified rate model for texture bits is derived using entropy. In addition, an analytic rate model for nontexture bits is proposed, which also takes into account the different characteristics of nontexture bits occurring in various depths of CUs in HEVC. The nontexture bitrates are modeled based on the linear relation between the total nontexture data and the dominant nontexture data in each CU category. Based on the proposed rate models for the texture and nontexture bits, accurate rate control can be achieved owing to more precise rate estimation. The experimental results show that the proposed rate control scheme achieves the average PSNR with 0.44 dB higher and the average PSNR standard deviation of 0.32 point lower with the buffer status levels maintained very close to target buffer levels, compared to the conventional methods. Finally, the proposed rate control scheme remarkably outperforms the conventional schemes especially for the sequences of complex texture and large motion. [ABSTRACT FROM PUBLISHER]

High Efficiency Video Coding (HEVC), a new video coding standard currently being established, adopts a quadtree-based Coding Unit (CU) block partitioning structure that is flexible in adapting various texture characteristics of images. However, this causes a dramatic increase in computational complexity compared to previous video coding standards due to the necessity of finding the best CU partitions. In this paper, a fast CU splitting and pruning method is presented for HEVC intra coding, which allows for significant reduction in computational complexity with small degradations in rate-distortion (RD) performance. The proposed fast splitting and pruning method is performed in two complementary steps: 1) early CU split decision and 2) early CU pruning decision. For CU blocks, the early CU splitting and pruning tests are performed at each CU depth level according to a Bayes decision rule method based on low-complexity RD costs and full RD costs, respectively. The statistical parameters for the early CU split and pruning tests are periodically updated on the fly for each CU depth level to cope with varying signal characteristics. Experimental results show that our proposed fast CU splitting and pruning method reduces the computational complexity of the current HM to about 50% in encoding time with only 0.6% increases in BD rate. [ABSTRACT FROM PUBLISHER]

In this paper, a fast mode decision method for the spatial higher layers (SHLs) in scalable video coding (SVC) is proposed based on coding dependency between two adjacent spatial lower and higher layers. The proposed fast mode decision method detects zero motion and zero transform coefficient blocks in the current spatial layer using the already encoded information of the corresponding blocks from the lower layer. The information for zero motion vectors and zero transform coefficients is used to induce a reduced set of candidate modes in SHLs of SVC, which reduces the computation complexity up to about 75% of the total encoding time while maintaining the coding performance with negligible amounts of degradation in peak signal-to-noise ratio values and bitrates. [ABSTRACT FROM PUBLISHER]