Intra frame coding for Advanced Video Coding Standard H.264 to control PSNR and reduce bit rate using Horizontal mode

In the high-efficiency video coding (HEVC) standard, intra prediction has higher computational complexity compared with H.264/AVC (advanced video coding) because of increasing the number of intra prediction modes and also higher number of coding unit (CU) sizes. The HEVC encoder evaluates 35 prediction modes on five possible prediction unit (PU) sizes to find the one with the minimum rate–distortion cost. Although this approach improves coding efficiency, it is very time-consuming. In this paper, we propose a fast intra prediction method to reduce the complexity of I-frame coding. The proposed method consists of three stages which is based on smoothness spatial feature. In the first stage, a measure is introduced to estimate CU smoothness by using sum of absolute differences (SAD) among CU pixels in four directions. By considering that a smooth region can be predicted with larger CUs, when the measured smoothness parameter is lower than a predefined threshold, only the prediction modes in the current CU are evaluated. In the second stage, the number of intra prediction modes is reduced based on the calculated SADs in the previous stage. In the last stage, if the first three candidate modes resulted from rough mode decision stage in the previous PU and the current PU are similar, then the best mode prediction of the previous PU is selected as the best candidate mode. Experimental results indicate that the proposed method can reduce the coding time on average to 43 % and maintain coding video quality, whereas bitrate increases negligibly (0.5 %).

Compared with Advanced Video Coding (AVC), High Efficiency Video Coding (HEVC) standard has higher compression ratio under the same reconstructed video quality. The improvement of coding ability depends on the introduction of many new coding technologies, such as flexible quadtree structure and more prediction modes. However, these coding tools also bring great computational complexity, which brings challenges to the real-time application of HEVC. Therefore, reducing the computational complexity of HEVC is a very meaningful topic. In this paper, firstly, we use Binary Sum of Absolute Difference (BSAD) to divide Coding Tree Unit (CTU) into three different types, namely static region, moving object boundary and moving object interior. Then, we utilize the depth distribution characteristics of different types to predict the depth range of Coding Tree Unit (CTU). Experimental results show that the proposed algorithm can effectively avoid unnecessary depth traversal, save 48.75% of coding time on average, and only increase the bitrate by 0.98%.

H.264/AVC, the latest video coding standard, adopts rate-distortion optimization (RDO) technique to obtain the best intra- and inter-prediction, while maximizing visual quality and minimizing the required bitrate. However, the full RD cost calculation for all intra-prediction modes, the exhaustive searches for finding optimal motion vectors for all block sizes, and the multiple references frame procedure considerably increase its computational complexity with the allowed number of prediction modes. The authors have previously proposed an approach for both inter- and intra-mode decisions that takes into account the several effective parameters, image content type, quantization parameter, correlation of motion vectors and motion details of video objects. In order to reduce the complexity, here we propose a new two-step adaptive search range decision by developing a combination of previous algorithm. The first step of our adaptive search range decision determines the search range for current MB according to the motion vectors of the previous MBs. In the second step, the motion vector obtained in the current frame is used to adaptively searching the window size of the previous reference frame for multi-frame motion estimation. As such, only a subset of inter- and intra-modes is chosen for RDO calculation. Experimental results show that the proposed algorithm reduces the total encoding cost with negligible loss in PSNR and a slightly increase in the required bitrate, when compared to our previous algorithm and other algorithms reported in the literature.

The latest video-coding standard H.264/AVC, which adopts rate distortion optimization (RDO), can achive better coding efficiency. However, several techniques, such as inter mode and intra mode selection need to check all the prediction modes. So, it will greatly increase computational complexity. In this paper, a fast algorithm based on the quantization parameter and the macroblock motion characteristics was proposed to reduce the compoexity of the encoder. The results show that this fast algorithm can reduces about 60.636% computing time than the full search algorithm with only 0.056dB loss in PSNR and 0.37% increment on the total bit.

Detection of fake high definition for HEVC videos based on prediction mode feature

Intra coding is used for reducing the spatial redundancy in video coding. H.264/MPEG-4 advanced video coding (AVC) supports several types of macroblock (MB) mode for Intra coding. Also, each of these MB modes has several directional prediction modes, which significantly improve the Intra coding efficiency, but also increase the encoding complexity. In this letter, we present an adaptive single-multiple prediction method for H.264/AVC Intra coding that not only improves the coding efficiency, but also reduces the encoding complexity. The proposed method adaptively skips the prediction mode bits, so that the encoder complexity can be reduced. The experimental results show that the proposed method achieves a bit-rate reduction of 3.58% and encoding time reduction of 42.4%.

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MPEG-4 파트 2에서 화질 확장성을 지원하는 FGS (fine granularity scalability) 코딩 기법은 가변적인 네트워크 대역폭에서 최적의 화질을 구현할 수 있는 스케일러블 비디오 코딩 기법이다. 본 논문에서는 기본 FGS 코딩 구조의 향상 계층에서, 영상의 잔여 신호를 다시 한 번 더 비트 평면 (bit-plane) 코딩을 해주는 FGS 코딩 구조를 제안하였다. 실험에서는 제안된 FGS 코딩 구조와 MPEG-4 VM (verification model) FGS 코딩 구조를 비교하여 제안된 FGS 코딩 구조의 화질 확장성을 평가하였다. 비교는 테스트된 3개의 비디오의 PSNR의 분석으로 이루어졌다. 결과는 제안된 구조가 비트율 제어 기법 VM5+를 이용했을 때, VM-FGS 코딩 구조보다 Y, U, V PSNR이 평균적으로 각각 0.4 dB, 9.4dB, 9 dB 더 높게 나타났고, QP (quantization parameter) 값을 17로 고정시킨 경우는, 제안된 구조가 4.61 dB, 20.21 dB, 16.56 dB 더 높게 나타났다. 결과에 의해, 제안된 구조가 VM-FGS 코딩 구조보다 최저부터 최대의 화질을 얻을 수 있는 화질 확장성이 더 높은 구조임을 알 수 있었다. FGS (fine granularity scalability) supporting scalability in MPEG-4 Part 2 is a scalable video coding scheme that provides bit-rate adaptation to varying network bandwidth thereby achieving of its optimal video quality. In this paper, we proposed FGS coding scheme which performs one more bit-plane coding for residue signal occured in the enhancement-layer of the basic FGS coding scheme. The experiment evaluated in terms of video quality scalability of the proposed FGS coding scheme by comparing with FGS coding scheme of the MPEG-4 verification model (VM-FGS). The comparison was conducted by analysis of PSNR values of three tested video sequences. The results showed that when using rate control algorithm VM5+, the proposed FGS coding scheme obtained Y, U, V PSNR of 0.4 dB, 9.4 dB, 9 dB averagely higher and when using fixed QP value 17, obtained Y, U, V PSNR of 4.61 dB, 20.21 dB, 16.56 dB averagely higher than the existing VM-FGS. From results, we found that the proposed FGS coding scheme has higher video quality scalability to be able to achieve video quality from minimum to maximum than VM-FGS.

This paper presents the design of a Human Visual System (HVS) based video coder. In this work, a wavelet based transform coding method is adopted for coding the Intra frames instead of the DCT based scheme. The major aim of developing such a coder is to highlight the role of perceptual models in improving the reconstructed video quality. The perceptual aspects are incorporated in two parts of the video coder. First, vision models are incorporated into the coding structure of both the luma and chroma components of each I frame when represented using the YCbCr space, which improves the reconstructed video quality to a large extend. Second, a perceptual metric called Structural Similarity Index Measure (SSIM), is used as the cost function for fast motion estimation which improves the speed of processing and prediction. The performance of the proposed coder is compared with the standard video coder. The performance comparison of the proposed and the standard coders are done in terms PSNR and latest perceptual measures, such as SSIM and VSNR. Thus the proposed coder gives promising results and paves the way for new research directions.

The intra- and inter-prediction techniques have been effectively exploited in the H.264/AVC for significantly improving the coding efficiency. However, exhaustively searching for the optimal prediction mode vastly increases its computational complexity. To decrease the computational complexity of the mode decision process, a novel fast mode decision algorithm is proposed in this paper to speed up the encoding process by predicting the mode of the current macroblock based on the motion activity of the neighboring macroblocks. The proposed algorithm has two main stages. First, the SKIP mode is utilized as an early termination mechanism to terminate any further checking of other modes. This is quite effective for those regions with low-motion activity. If the SKIP mode is not met, the local macroblocks' motion activities will be identified in terms of motion-vector city-block length. Experimental results have shown that the proposed algorithm achieves a reduction of 56% computational complexity on average, while introducing only 0.059 dB loss in PSNR and 0.2% increment on the total bit rate compared with that of exhaustive trying out all possible modes, being set as the default in the original JM reference software.

In comparison with H.264/Advanced Video Coding, the newest video coding standard, High Efficiency Video Coding (HEVC), improves video coding rate-distortion (RD) performance, but at the price of significant increase in its encoding complexity, especially, in intra-mode decision due to the adoption of more complex block partitions and more candidate intra-prediction modes (IPMs). To reduce the mode decision complexity in HEVC intra-frame coding, while maintaining its RD performance, in this paper, we first formulate the mode decision problem in intra-frame coding as a Bayesian decision problem based on the newly proposed transparent composite model (TCM) for discrete cosine transform coefficients, and then present an outlier-based fast intra-mode decision (OIMD) algorithm. The proposed OIMD algorithm reduces the complexity using outliers identified by TCM to make a fast coding unit split/nonsplit decision and reduce the number of IPMs to be compared. To further take advantage of the outlier information furnished by TCM, we also refine entropy coding in HEVC by encoding the outlier information first, and then the actual mode decision conditionally given the outlier information. The proposed OIMD algorithm can work with and without the proposed entropy coding refinement. Experiments show that for the all-intra-main test configuration of HEVC: 1) when applied alone, the proposed OIMD algorithm reduces, on average, the encoding time (ET) by 50% with 0.7% Bjontegaard distortion (BD)-rate increase and 2) when applied in conjunction with the proposed entropy coding refinement, it reduces, on average, both the ET by 50% and BD-rate by 0.15%.

Video surveillance and its applications have become increasingly ubiquitous in modern daily life. In video surveillance system, video coding as a critical enabling technology determines the effective transmission and storage of surveillance videos. In order to meet the real-time or time-critical transmission requirements of video surveillance systems, the low-delay (LD) configuration of the advanced high efficiency video coding (HEVC) standard is usually used to encode surveillance videos. The coding efficiency of the LD configuration is closely related to the quantization parameter (QP) cascading technique which selects or determines the QPs for encoding. However, the quantization parameter cascading (QPC) technique currently adopted for the LD configuration in HEVC test model (i.e., HM) is not optimized since it has not taken full account of the reference dependency in coding. In this paper, an efficient QPC technique for surveillance video coding, referred to as QPC-SV, is proposed, considering all inter reference frames under the LD configuration. Experimental results demonstrate the efficacy of the proposed QPC-SV. Compared with the default configuration of QPC in the HM, the QPC-SV achieves significant rate-distortion performance gain with average BD-rates of -9.35% and -9.76% for the LDP and LDB configurations, respectively.

In H.264 advanced video coding (AVC), variable block size motion estimation plays an important role in compression of interframes. In this paper, we propose a fast inter prediction algorithm based on hierarchical homogeneous detection and cost analysis to select the best mode effectively. For each macroblock, we first detect that whether the macroblock is spatial homogeneous or not. For the non spatial homogeneous macroblock, we then perform the 16times16 motion estimation and examine if the 16times16 block is temporal homogeneous or not. Once the homogeneous macroblock is detected in the above process, the best mode will be chosen as 16times16 mode. For the non-homogeneous macroblock, we then execute 8times8 motion estimation and analyze the cost of 8times8 mode and 16times16 mode for deciding the best inter mode should be 16times16 mode or any other mode. The process for searching the best 8times8 block subtype is similar to the process for macroblocks. Finally, the best inter mode is decided by selecting the inter mode with least cost from the candidate modes. Experimental results show that our proposed algorithm can save about 32~54% computation time without introducing any noticeable performance degradation

High Efficiency Video Coding (HEVC), a successor to H.264, is the next generation video compression standard. To enhance the coding efficiency of video frames, 35 intra prediction modes adopted in Prediction Unit (PU) from 4×4 to 64×64 of HEVC. However the improvement is based on the cost of rapid increased complexity. This paper proposes a fast mode and depth decision algorithm based on edge detection and reconfiguration to alleviate the large computation complexity in intra prediction with the trivial degradation in the accuracy. In mode decision, pixel gradient statistics (PGS) and mode refinement (MR) is proposed. PGS use pixel gradient information to assist prediction mode selection after Rough Mode Decision (RMD). MR utilizes the neighboring mode information to select most probable mode (MPM). In depth decision, unit partitioning reconfiguration (UPR) is proposed. It exchanged the original partitioning order in a more reasonable structure, utilizes detecting the smoothness of coding unit to decide the prediction depth. Smoothness detecting is based on PGS result. Experiment result shows that the proposed method performs about 42.84% time saving with little degradation (BD-rate increase 0.61% and BDPSNR reduce 0.041db) in the coding gain. Comparing with previous work, it achieves more time saving and lesser efficiency loss.

3D-HEVC is developed by ISO/IEC MPEG and ITU-T Video Coding Experts Group (VCEG) as the highestprofile extension of HEVC for 3D video coding and Multi-View texture Videos plus Depth maps (MVD) compress. Concerning the current 3D-HEVC design, the uniform HEVC Intra prediction and Depth Modeling Modes (DMMs) are used in a sophisticated way to ameliorate the performance of the depth map video coding. Although, the enhancement of the coding efficiency is achieved at the cost of computational complexity load, which prevents 3D-HEVC from being used in real-world applications. Thus, we suggest a fast depth map Intra prediction mode decision based on the Self-organizing Map to resolve the aforementioned computational complexity increases. The experimental results demonstrate that the suggested algorithm can increase the encoding time savings up to 39.8%, with insignificant rate-distortion loss.