Rate-distortion Optimization Technique Research Articles

Adaptive HEVC video steganograhpy based on PU partition modes

High EfficiencyVideoCoding (HEVC) −based steganography has gained attention as a prominent research focus. Especially, block structure based HEVC video steganography has received increasing attention due to commendable performance. However, current block structure- based steganography algorithms confront with challenges such as reduced coding efficiency and limited capacity. To avoid these problems, an adaptive video steganography algorithm based on Prediction Unit (PU) partition mode in I-frames is proposed. This is done through the analysis of the block division process and the visual distortion resulting from the modification of the PU partition mode in HEVC. The PU block structure is utilized as steganographic covers, and the Rate Distortion Optimization (RDO) technique is introduced to establish an adaptive distortion function for Syndrome-trellis code (STC). Further comparison is performed between the proposed method and the state-of-the-art steganography algorithms, confirming its advantages in embedding capacity, compression efficiency, visual quality, and resistance to video steganalysis.

High Speed Coding Unit Depth Identification Based on Texture Image Information Using SVM

High-Efficiency Video Coding (HEVC/H.265) is a new video coding standard with half the bit rate of its predecessor, Advanced Video Coding (AVC/H.264). AVC/H.264 uses macroblocks, processing units between 4×4 and 16×16 pixels in size. H.265 uses Coding Tree Units (CTUs), a more complicated block structure that lets images be as large as 64×64 pixels. However, changing from macroblocks to coding tree units is essential for H.265 to become more efficient. Using the quadtree structure to divide the Coding Unit (CU) makes it harder for HEVC to find the optimal rate distortion. This paper presents a Support Vector Machine (SVM)-based method for finding the fastest coding unit division in intra-prediction HEVC without compromising compression efficiency. All partitions of CTU are assessed using five characteristics: Standard Deviation (SD), Root Mean Square Error (RMSE), Sub CU Complexity Difference (SCCD), Directional Complexity (DC), and Quantization Parameter (QP) to optimize the intra-prediction of HEVC in all intra-configurations. Simulations have been carried out to estimate the performance of the proposed machine learning-based algorithm using test sequences with different resolutions. Simulation results have shown that combining directional complexity and standard deviation gives a more accurate classification. SVM has been used to separate split-unsplit samples, and the standard rate-distortion optimization technique has been used to separate samples that are hard to separate. The results have shown a reduction of 67.44% in encoding time with a slight increase in bit rate.

Blind MV-based video steganalysis based on joint inter-frame and intra-frame statistics

Despite all its irrefutable benefits, the development of steganography methods has sparked ever-increasing concerns over steganography abuse in recent decades. To prevent the inimical usage of steganography, steganalysis approaches have been introduced. Since motion vector manipulation leads to random and indirect changes in the statistics of videos, MV-based video steganography has been the center of attention in recent years. In this paper, we propose a 54-dimentional feature set exploiting spatio-temporal features of motion vectors to blindly detect MV-based stego videos. The idea behind the proposed features originates from two facts. First, there are strong dependencies among neighboring MVs due to utilizing rate-distortion optimization techniques and belonging to the same rigid object or static background. Accordingly, MV manipulation can leave important clues on the differences between each MV and the MVs belonging to the neighboring blocks. Second, a majority of MVs in original videos are locally optimal after decoding concerning the Lagrangian multiplier, notwithstanding the information loss during compression. Motion vector alteration during information embedding can affect these statistics that can be utilized for steganalysis. Experimental results have shown that our features’ performance far exceeds that of state-of-the-art steganalysis methods. This outstanding performance lies in the utilization of complementary spatio-temporal statistics affected by MV manipulation as well as feature dimensionality reduction applied to prevent overfitting. Moreover, unlike other existing MV-based steganalysis methods, our proposed features can be adjusted to various settings of the state-of-the-art video codec standards such as sub-pixel motion estimation and variable-block-size motion estimation.

Early Termination of Intra Mode Decision Based on Most Probable Mode and SATD for H.264/AVC encoding

Intra coding in H.264/AVC can significantly improve the coding efficiency but at the cost of high computational complexity due to the use of rich prediction modes and rate-distortion optimization technique. In this paper, an early termination algorithm of intra mode decision is presented to address the complexity issue in 4×4 intra prediction. The proposed algorithm is motivated by two facts: the most probable mode defined based on the spatial similarity has a high possibility to be the best mode, and a good prediction usually has a small residual block which is measured by the sum of absolute transformed difference (SATD). The most probable mode and two modes with the smallest SATD values are investigated to select the candidate modes by using the proposed early termination rules. Experimental results show that the proposed algorithm effectively reduces the complexity of 4×4 intra prediction while maintaining almost the same coding performance on peak signal-to-noise ratio and bit rate compared with the full search algorithm.

Video analytical coding: When video coding meets video analysis

Leveraging on the properties of human visual system, most of the well-designed video coding standards utilize rate–distortion optimization techniques by maximizing a fidelity cost function (e.g., peak signal noise ratio, PSNR) under an available bit rate budget constrain. However, a huge amount of video data is consumed by computers rather than by human beings in several application scenarios. In view of this, this paper proposes a new coding framework called video analytical coding (VAC) for video analysis. We use the term “analytical distortion” to denote the difference of video analysis performance when video quality degrades and analytical distortion is estimated by compression distortion. Meanwhile, we develop a new rate–analytical-distortion optimization (RADO) method to trade off the bit rate and the analytical distortion. Specifically, we consider moving object detection as the analysis task and develop a rate analytical distortion (RAD) model and a quantization parameter adaptation strategy for video coding, where the analytical distortion is related to the object detection performance represented as F1-measure. Experimental results show that the performance of the video analysis task can be significantly improved (up to 40% reduction of analytical distortion).

A fast intra mode decision algorithm combining neighboring information for H.264/AVC high profile

Intra coding in H.264/AVC can significantly improve the coding efficiency but at the cost of high computational complexity due to the use of rich prediction modes and rate-distortion optimization technique. To reduce the complexity, this paper proposes a fast mode decision algorithm for intra prediction in H.264/AVC high profile. The best prediction mode not only relies on the content of current block but also depends on the neighboring blocks because of the spatial continuity. Based on the reconstructed neighboring pixels, different prediction mode leads to different residual block which is the difference between the original block and predicted block. Since small residual block is advantageous to get good coding including the small distortion and few bit numbers, the feature from the residual block will be used to help do mode decision. Besides the neighboring pixels, the best modes of encoded neighboring blocks are also used to select the candidate modes. The proposed algorithm uses the sum of absolute transformed difference (SATD) to measure the residual block and uses the most probable mode to indicate the influence of the prediction modes of the neighboring blocks. Based on the statistic on mode decision accuracy, the most probable mode and the modes with the smallest residual block are considered as the candidate modes. Meanwhile, the early termination rules which can directly select only one mode are given in the proposed algorithm. Experimental results show that the proposed algorithm effectively reduces the complexity of intra prediction with slight coding performance degradation compared with the full search algorithm.

Towards an FPGA-Based HEVC Encoder: A Low-Complexity Rate Distortion Scheme for AMVP

Advanced motion vector prediction (AMVP) is a new technique adopted in the latest high efficiency video coding (HEVC) standard. AMVP block predicts an initial motion vector of the current block from a given set of candidates by means of rate distortion (RD) optimization process. Due to the large number of different-sized blocks, simplification of RD optimization process in AMVP block is highly appreciated. Therefore, we present a new RD optimization technique for AMVP block in HEVC encoder. The proposed RD calculation approach finds the best AMVP candidate by processing less number of feature pixels per every block. Experimental results show notable speedup in terms of AMVP processing time with tolerable quality degradation (PSNR) and bitrate requirement. The proposed RD calculation technique reduces the RD computational complexity of the AMVP block by 87.5% as maximum (i.e. 1.7% of the whole encoder complexity). This improvement is accompanied with a modest average PSNR loss of 0.10 dB and an increase by 2.4% in terms of bitrate. On the other hand, we present an FPGA-based architecture for AMVP unit in HEVC encoder. The proposed architecture was prototyped, simulated and synthesized on Xilinx Virtex-7 XC7VX550T FPGA. At 188 MHz clock frequency, the proposed architecture processes 8 K (7680 \(\times \) 4320) YCrCb resolution at 60 fps while utilizing less than 1% of the FPGA resources.

Low complexity encoder optimization for HEVC

High Efficiency Video Coding (HEVC) improved the coding efficiency significantly. Compared to its predecessor H.264/AVC, it can provide equivalent subjective quality with more than 57% bit rate reduction. However, the improvement on coding efficiency is obtained at the expense of much more intensive computation complexity. In this paper, based on an overall analysis of computation complexity at the HEVC encoder, a low complexity encoder optimization scheme is proposed by reducing the number of available candidates for evaluation in terms of the intra prediction mode decision, early termination of coding unit (CU) splitting and adaptive reference frame selection. With the proposed scheme, the rate distortion optimization (RDO) technique of HEVC can be implemented in a low-complexity way for complexity-constrained encoders. Experimental results demonstrate that, compared with the original HEVC reference encoder implementation, the proposed optimization scheme can achieve more than 40% complexity reduction on average with coding performance degradation as only 0.43% which can be ignorable.

Fast TU size decision algorithm for HEVC encoders using Bayesian theorem detection

The emerging internationalhigh efficiency video coding (HEVC) uses variable block-size transform coding of the prediction error residual. The residual block is partitioned into multiple square transform units. The supported transform unit (TU) sizes are 4×4, 8×8, 16×16, and 32×32. The optimal TU size is chosen based on rate distortion optimization techniques. Variable TU sizes have a coding performance superior to the traditional fixed-block-size transform. Meanwhile, it causes high computational complexity at the encoder. In this paper, we propose an early termination algorithm of TU size decision for HEVC encoders. The proposed method uses the Bayesian decision theory and the correlation between the variance of residual coefficients and the transform size to reduce the number of candidate transform sizes for a given block. Simulation results show that the proposed algorithm can save 30–46% of transform processing complexity with negligible loss of coding efficiency.

Adaptive transform size decision algorithm for high-efficiency video coding inter coding

Variable transform sizes have been adopted by the emerging international standard of high-efficiency video coding (HEVC). The HEVC test model (HM) supports four different transform sizes in the range of 4×4 to 32×32. The transform size is chosen based on the rate-distortion optimization techniques. Variable transform sizes have a coding performance superior to the traditional fixed block-size transform. Meanwhile, this causes high computational complexity at the encoders. We propose a fast transform size decision algorithm incorporating three methods: (1) transform bypass based on the SKIP mode detection, (2) content-based transform size decision, and (3) early termination of variable-sized transform. The proposed algorithm first checks coding information from nearby spatially and temporally coding units (CUs) or treeblocks and the parent CU in the upper depth level. Based on the coding information from nearby CUs, only a small number of transform sizes are selected in the procedure of transform size decision. Simulation results show that our algorithm can reduce the complexity of the transform procession by more than 55% with a negligible loss of coding efficiency.

High-Efficiency Mode Decision Procedure for H.264/AVC Under Cloud Computing Environments

The latest video coding standard, H.264/AVC, could achieve higher encoding performance compared with previous versions since it employs many tools to increase the coding accuracy, particularly the rate-distortion optimization technique for mode decision. However, enormous computational complexity is produced because all possible combinations of modes are calculated in order to find the optimal Rate-Distortion Cost, which will bring huge computational stress, particularly under cloud computing environments. To conquer this problem, a high-efficiency mode decision procedure for H.264/AVC under cloud computing environment is proposed in this paper. First, a fast intramode-type selection algorithm is presented to determine the intraprediction block size in advance. Then, the original multiple mode candidates for each prediction type are reduced at least by half with the information abstracted from macroblock and its 4×4 subblocks. The simulation results show that the proposed algorithm could reduce around 84% encoding time in average while maintaining the encoding performance efficiently with slight decrease in peak signal-to-noise ratio and increase in bit rate compared with H.264 reference software. It also produces better coding efficiency compared with the existing novel algorithms and could be widely used for multimedia communication systems with H.264/AVC standard under cloud computing environments.

Fast Mode Decision and Encryption Policy in H.264/AVC Frame-skipping Transcoding

H.264/AVC adopts Rate-Distortion Optimization (RDO) techniques to search all the prediction modes supported by standard in turn, then determine the optimal encoding mode which has the minimum rate-distortion cost. Frame-skipping transcoding among heterogeneous networks is a way to lower bitrate transcoding, which can solve incompatibility issues of video stream transmission. Aiming to varied motion problem of the video sequences, this paper introduces a set of adaptive threshold for inter mode decision, which can make a more correct code judgment of motion characteristics for the macroblock, also can obtain more reliable video quality; Combing the mode information of the skipping frame which can not be recovered, a simple and practicable encryption policy is introduced here, which avoids the shortcomings of traditional encryption algorithm complexity. Experimental results show that the encoding time of the new algorithm is almost the same with that of the referenced algorithm, the peak value SNR increases steadily, so novel scheme guarantees nice video quality; Encryption policy achieves the desired encryption effect and efficiency, and broadens the applications of the video security technology.

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.

2-Step Scalar Deadzone Quantization for Bitplane Image Coding

Modern lossy image coding systems generate a quality progressive codestream that, truncated at increasing rates, produces an image with decreasing distortion. Quality progressivity is commonly provided by an embedded quantizer that employs uniform scalar deadzone quantization (USDQ) together with a bitplane coding strategy. This paper introduces a 2-step scalar deadzone quantization (2SDQ) scheme that achieves same coding performance as that of USDQ while reducing the coding passes and the emitted symbols of the bitplane coding engine. This serves to reduce the computational costs of the codec and/or to code high dynamic range images. The main insights behind 2SDQ are the use of two quantization step sizes that approximate wavelet coefficients with more or less precision depending on their density, and a rate-distortion optimization technique that adjusts the distortion decreases produced when coding 2SDQ indexes. The integration of 2SDQ in current codecs is straightforward. The applicability and efficiency of 2SDQ are demonstrated within the framework of JPEG2000.

Fast Inter Mode Decision Algorithm Based on Mode Mapping and Decision Tree for P Frames in MPEG-2 to H.264/AVC Transcoding

There is an inevitable requirement of transcoding from MPEG-2 to H.264/AVC in many video applications. Due to the use of variable block sizes and rate-distortion optimization techniques in H.264, t...

An efficient mode decision algorithm for H.264/AVC intra prediction

Rate distortion optimization technique is adopted by H.264/AVC to select the best intra and inter prediction modes. It achieves remarkable improvement in compression performance, but the computational complexity of coding increases greatly. In order to reduce the computational complexity as much as possible while guaranteeing the video encoding quality and compression efficiency, this paper proposes a fast mode decision method based on the texture direction information of intra prediction modes and the encoding macroblocks. For intra luminance prediction, the proposed algorithm utilizes the smoothness of the encoding macroblock to select the suitable intra prediction block sizes, and then uses the texture direction difference to filter out low possibility prediction modes. The calculation expressions of texture direction difference can be derived by extracting texture direction features from intra prediction modes. For intra chrominance prediction, the candidate prediction modes are determined by a combination of texture direction difference and the sum of absolute transformed difference, which doesn't significantly degrade peak-signal-noise-rate or increase bit rate. Based on the processing, the number of rate distortion cost calculations decreases dramatically, which indicates a significant reduction of computation cost for intra prediction. Compared with JM11.0 reference software, the proposed algorithm can cut down about 76.79 % total intra-frame coding time at the expense of only about 0.08 dB peak-signal-noise-rate degradation and 2.07 % bit rate increase. It proves that the proposed algorithm achieves a tradeoff between the rate distortion performance and the computational complexity.

Enhanced Inter-Prediction Via Shifting Transformation in the H.264/AVC

Inter-prediction based on block-based motion estimation (ME) is used in most video codecs. The closer the prediction to the target block, the lower the residual, and thus more efficient compression can be achieved. In this paper, a new technique called enhanced inter-prediction (EIP) is proposed to improve the prediction candidates using an additional transformation acting while performing ME. A parametric transformation acts within the coding loop of each block to modify the prediction for each motion vector candidate. The EIP is validated in the particular case of a single-parameter shifting transformation. This paper presents an efficient algorithm to compute the best shift for each prediction candidate and a model to select the optimal prediction based on minimum cost integrating the approach with existing rate-distortion optimization techniques in the H.264/AVC video codec. Results show significant improvements with an average of 6% bit-rate reduction compared to the original H.264/AVC.

Fast coding unit selection method for high efficiency video coding intra prediction

The high efficiency video coding (HEVC) video coding standard under development can achieve higher compression performance than previous standards, such as MPEG-4, H.263, and H.264/AVC. To improve coding performance, a quad-tree coding structure and a robust rate-distortion (RD) optimization technique is used to select an optimum coding mode. Since the RD costs of all possible coding modes are computed to decide an optimum mode, high computational complexity is induced in the encoder. A fast learning-based coding unit (CU) size selection method is presented for HEVC intra prediction. The proposed algorithm is based on theoretical analysis that shows the non-normalized histogram of oriented gradient (n-HOG) can be used to help select CU size. A codebook is constructed offline by clustering n-HOGs of training sequences for each CU size. The optimum size is determined by comparing the n-HOG of the current CU with the learned codebooks. Experimental results show that the CU size selection scheme speeds up intra coding significantly with negligible loss of peak signal-to-noise ratio.

Fast mode decision algorithm for scalable video coding based on luminance coded block pattern

A fast mode decision algorithm is proposed to reduce the com- putation complexity of adaptive inter layer prediction method, which is a motion estimation algorithm for video compression in scalable video cod- ing (SVC) encoder systems. SVC is standard as an extension of H.264/ AVC to provide multimedia services within variable transport environments and across various terminal systems. SVC supports an adaptive inter mode prediction, which includes not only the temporal prediction modes with varying block sizes but also inter layer prediction modes based on correlation between the lower layer information and the current layer. To achieve high coding efficiency, a rate distortion optimization technique is employed to select the best coding mode and reference frame for each MB. As a result, the performance gains of SVC come with increased com- putational complexity. To overcome this problem, we propose fast mode decision based on coded block pattern (CBP) of 16 × 16 mode and refer- ence block of best CBP. The experimental results in SVC with combined scalability structure show that the proposed algorithm achieves up to an average 61.65% speed up factor in the encoding time with a negligible bit increment and a minimal image quality loss. In addition, experimental results in spatial and quality scalability show that the computational com- plexity has been reduced about 55.32% and 52.69%, respectively. © 2013

Motion Estimation Without Integer-Pel Search

The typical motion estimation (ME) consists of three main steps, including spatial-temporal prediction, integer-pel search, and fractional-pel search. The integer-pel search, which seeks the best matched integer-pel position within a search window, is considered to be crucial for video encoding. It occupies over 50% of the overall encoding time (when adopting the full search scheme) for software encoders, and introduces remarkable area cost, memory traffic, and power consumption to hardware encoders. In this paper, we find that video sequences (especially high-resolution videos) can often be encoded effectively and efficiently even without integer-pel search. Such counter-intuitive phenomenon is not only because that spatial-temporal prediction and fractional-pel search are accurate enough for the ME of many blocks. In fact, we observe that when the predicted motion vector is biased from the optimal motion vector (mainly for boundary blocks of irregularly moving objects), it is also hard for integer-pel search to reduce the final rate-distortion cost: the deviation of reference position could be alleviated with the fractional-pel interpolation and rate-distortion optimization techniques (e.g., adaptive macroblock mode). Considering the decreasing proportion of boundary blocks caused by the increasing resolution of videos, integer-pel search may be rather cost-ineffective in the era of high-resolution. Experimental results on 36 typical sequences of different resolutions encoded with x264, which is a widely-used video encoder, comply with our analysis well. For 1080p sequences, removing the integer-pel search saves 57.9% of the overall H.264 encoding time on average (compared to the original x264 with full integer-pel search using default parameters), while the resultant performance loss is negligible: the bit-rate is increased by only 0.18%, while the peak signal-to-noise ratio is decreased by only 0.01 dB per frame averagely.