Target Bit Rate Research Articles

Region-based rate control for 3D-HEVC based texture video coding

Bit starvation resulted from inefficient rate control of 3D video coding deteriorates visual quality of synthesized views. Most region based rate control schemes allocate higher bitrate to regions of interest (ROIs), but bits may be still consumed by early coded units. This paper avoids reducing coding bits in high-cost regions of 3D-HEVC. Instead of ROIs that are determined by humans, high-cost regions sensitive to bit starvation are detected. Region-level bit allocation is achieved by curve fitting of coding statistics, and recursive Taylor expansion (RTE) based bit allocation is adopted to optimally estimates the target bitrate and the QP related λ of LCUs in each region. Based on retained earnings in economics, bits are reserved for LCUs that are sensitive to distortions. Experimental results show that the proposed scheme outperforms both the R-λ model and RTE model in bitrate accuracy with similar R-D performance.

Graph-Based Rate Control in Pathology Imaging With Lossless Region of Interest Coding.

The increasing availability of digital pathology images has motivated the design of tools to foster multidisciplinary collaboration among researchers, pathologists, and computer scientists. Telepathology plays an important role in the development of collaborative tools, as it facilitates the transmission and access to pathology images by multiple users. However, the huge file size associated with pathology images usually prevents full exploitation of the collaborative telepathology system potential. Within this context, rate control (RC) is an important tool that allows meeting storage and bandwidth requirements by controlling the bit rate of the coded image. In this paper, we propose a novel graph-based RC algorithm with lossless region of interest (RoI) coding for pathology images. The algorithm, which is designed for block-based predictive transform coding methods, compresses the non-RoI in a lossy manner according to a target bit rate and the RoI in a lossless manner. It employs a graph where each node represents a constituent block of the image to be coded. By incorporating information about the coding cost similarities of blocks into the graph, a graph kernel is used to distribute a target bit budget among the non-RoI blocks. In order to increase RC accuracy, the algorithm uses a rate-lambda (R- ) model to approximate the slope of the rate-distortion curve of the non-RoI, and a graph-based approach to guarantee that the target bit rate is accurately attained. The algorithm is implemented in the High-Efficiency Video Coding standard and tested over a wide range of pathology images with multiple RoIs. Evaluation results show that it outperforms the other state-of-the-art methods designed for single images by very accurately attaining the target bit rate of the non-RoI.

Highly Spectrally Efficient Discrete Multi-Tone Transmission over Step Index PMMA optical fibre for Short-Range Optical Communication

In this article we present high spectral efficiency DMT transmissions over 20 m of Step-Index polymethyl methacrylate optical fiber in the visible range. We demonstrated that using illumination light emitting diodes at 450, 520, 560 and 650 nm it is possible to achieve as high as 6.39 bits/s/Hz for a pre- Forward Error Correction with a target Bit Error Rate of 10-3. The optical source at 560 nm was developed in our laboratory and then we demonstrated its usage as a new channel in WDM system.

Reduction of computation time in differential evolution-based quantisation table optimisation for the JPEG baseline algorithm

The design of quantisation table is viewed as an optimisation problem because the quantisation table produces the compression/quality trade-off in baseline joint photographic experts group algorithm. In this paper, efforts have been taken to reduce the computation time of the differential evolution (DE) algorithm by using the surrogate model. This paper applies a problem approximation surrogate model (PASM) to assist DE algorithms for optimising the quantisation table. It also analyses the performance of PASM in DE algorithm based on approximation error and evolutionary perspective. In addition, it confirms the results using statistical hypothesis tests. PASM is integrated in classical differential evolution and knowledge-based differential evolution algorithms. Different benchmark images are used to validate the PASM performance in DE algorithms for three target bits per pixel. The result shows that integrated PASM in DE algorithms reduces the computation time and guarantees the similar results as DE algorithms without a model.

$\lambda $ -Domain Optimal Bit Allocation Algorithm for High Efficiency Video Coding

Rate control typically involves two steps: bit allocation and bitrate control. The bit allocation step can be implemented in various fashions depending on how many levels of allocation are desired and whether or not an optimal rate–distortion (R-D) performance is pursued. The bitrate control step has a simple aim in achieving the target bitrate as precisely as possible. In our recent research, we have developed a $ {\lambda }$ -domain rate control algorithm that is capable of controlling the bitrate precisely for High Efficiency Video Coding (HEVC). The initial research showed that the bitrate control in the $ {\lambda }$ -domain can be more precise than the conventional schemes. However, the simple bit allocation scheme adopted in this initial research is unable to achieve an optimal R-D performance reflecting the inherent R-D characteristics governed by the video content. In order to achieve an optimal R-D performance, the bit allocation algorithms need to be developed taking into account the video content of a given sequence. The key issue in deriving the video-content-guided optimal bit allocation algorithm is to build a suitable R-D model to characterize the R-D behavior of the video content. In this paper, to complement the R- $ {\lambda }$ model developed in our initial work, a D- $ {\lambda }$ model is properly constructed to complete a comprehensive framework of $ {\lambda }$ -domain R-D analysis. Based on this comprehensive $ {\lambda }$ -domain R-D analysis framework, a suite of optimal bit allocation algorithms are developed. In particular, we design both picture-level and basic-unit-level bit allocation algorithms based on the fundamental R-D optimization theory to take full advantage of the content-guided principles. The proposed algorithms are implemented in HEVC reference software, and the experimental results demonstrate that they can achieve an obvious R-D performance improvement with a smaller bitrate control error. The proposed bit allocation algorithms have already been adopted by the Joint Collaborative Team on Video Coding and integrated into the HEVC reference software.

SSIM-Motivated Two-Pass VBR Coding for HEVC

We propose a structural similarity (SSIM)motivated two-pass variable bit rate control algorithm for High Efficiency Video Coding. Given a bit rate budget, the available bits are optimally allocated at group of pictures (GoP), frame, and coding unit (CU) levels by hierarchically constructing a perceptually uniform space with an SSIM-inspired divisive normalization mechanism. The Lagrange multiplier λ, which controls the tradeoff between perceptual distortion and bit rate, is adopted as the GoP level complexity measure. To derive λ, Laplacian distribution-based rate and perceptual distortion models are established after the first pass encoding, and the target bits are dynamically allocated by maintaining a uniform Lagrange multiplier level for each GoP through λ equalization. Within each GoP, rate control is further performed at frame and CU levels based on SSIM-inspired divisive normalization, aiming to transform the prediction residuals into a perceptually uniform space. Experiments show that the proposed scheme achieves high accuracy rate control and superior rate-SSIM performance, which is further verified by subjective visual testing.

Light Field Compression With Homography-Based Low-Rank Approximation

This paper describes a light field compression scheme based on a novel homography-based low-rank approximation method called HLRA. The HLRA method jointly searches for the set of homographies best aligning the light field views and for the low-rank approximation matrices. The light field views are aligned using either one global homography or multiple homographies depending on how much the disparity across views varies from one depth plane to the other. The light field low-rank representation is then compressed using high efficiency video coding (HEVC). The best pair of rank and quantization parameters of the coding scheme, for a given target bit rate, is predicted with a model defined as a function of light field disparity and texture features. The results are compared with those obtained by directly applying HEVC on the light field views restructured as a pseudovideo sequence. The experiments using different datasets show substantial peak signal to noise ratio (PSNR)-rate gain of our compression algorithm, as well as the accuracy of the proposed parameter prediction model, especially for real light fields. A scalable extension of the coding scheme is finally proposed.

Tile-level rate control for tile-parallelization HEVC encoders

In this paper, we propose a tile-level rate control algorithm for high efficiency video coding on tile-parallelization case. In general, conventional rate control algorithms consist of three stages: group-of-picture-level, picture-level, and unit-level rate controls. The proposed rate control algorithm embeds a tile-level rate control by adaptively assigning the appropriate bits for each tile according to the tile-level visual characteristics of the intrapictures. With respect to interpictures, the actual generated bits for all the tiles are collected and the target bits are allocated with actual generated bits from the collocated tile of the previously coded picture. Then, the rate control parameters are updated by averaging the updated block unit parameters in the tile. We evaluated the proposed algorithm using three different tile partition settings (four-, six-, and eight-tile partitions) with random access configuration. The experimental results show that the proposed tile-level rate control algorithm for tile-parallelization yields to outperform performances in terms BD-rate gain, visual quality, and bit accuracy as that of the sequential rate control model of HM-16.12.

Efficient frame‐level bit allocation algorithm for H.265/HEVC

Rate control (RC) plays a critical role in video coding for regulating the coded bit-stream to achieve the target bitrate, which involves two basic steps: bit allocation (BA) and quantisation parameter selection. Here, the former is a key element to directly affect the performance of RC. So, in this study, an efficient frame-level BA algorithm is proposed for the latest video coding standard H.265/high-efficiency video coding (HEVC). First, by analysing the optimisation problem of the frame-level BA, two factors have been found to be related to the frame-level BA, which are inter-frame dependency and the target bitrate. Then, a measure of inter-frame dependency is put forward to reflect the correlation among consecutive frames. Finally, according to the results of allocation weights through the dynamic programming method, the relationships among the allocation weights and the two factors are investigated, and based on which the efficient BA model is established. Experimental results show that in comparison with the original RC scheme in HM-14.0, the proposed frame-level BA algorithm reduces, on average, BD-rate by 5.19% with negligible encoding time increase. In addition, the proposed algorithm also achieves higher GOP-level RC accuracy compared with the original RC scheme in HM.

Inter-View Dependency-Based Rate Control for 3D-HEVC

We propose an inter-view dependency-based rate control (RC) algorithm for 3D extension of high efficiency video coding (HEVC). First, considering the rate-distortion (R-D) dependency between the synthesized views and the input views (including texture videos and depth maps), a synthesized view distortion model is derived. Second, a novel distortion model for dependent views is proposed by investigating the inter-view dependency between the base and dependent views. Based on these two distortion models, a joint optimal bit allocation strategy (including texture/depth level, view level, and frame level) is developed to allocate target bits for both texture videos and depth maps of different views. Furthermore, an effective initial quantization parameter decision scheme considering the characteristics of the input video content is presented. Extensive experimental results exhibit that the proposed scheme achieves a higher rate control accuracy and provides a better R-D performance than the state-of-the-art RC algorithms.

Channel-Adaptive Rate Control for Low Delay Video Coding

This paper presents a channel-adaptive rate control algorithm for low delay video coding. The main goal of the proposed method is to adaptively use the unknown available channel bandwidth while reducing the end-to-end delay between encoder and decoder. The key idea of the proposed algorithm is for the status of the encoder buffer to indirectly reflect the mismatch between the available channel bandwidth and the generated bitrate. Hence, the proposed method fully utilizes the unknown available channel bandwidth by monitoring the encoder buffer status. Simulation results show that although the target bitrate mismatches the available channel bandwidth, the encoder efficiently adapts the given available bandwidth to improve the peak signalto-noise ratio.

<inline-formula> <tex-math notation="LaTeX">$\lambda$</tex-math> </inline-formula>-Domain Rate Control Algorithm for HEVC Scalable Extension

In this paper, we propose a $\boldsymbol {\lambda }$ -domain rate control algorithm for high efficiency video coding (HEVC) scalable extension. All the commonly used scalabilities including temporal, spatial, and quality scalability are taken into consideration. The proposed algorithm mainly has three key contributions. First, we propose an optimal initial target bits and initial encoding parameters determination algorithm for the first frame of each layer to achieve the best rate-distortion (R-D) performance. Second, an optimal bit allocation algorithm taking both the intra and inter layer dependence into consideration is proposed for the inter frames under spatial and quality scalability cases. Third, since the coding scheme of HEVC scalable extension with multiple layers is even more flexible than HEVC, an adaptive updating algorithm for R- $\boldsymbol {\lambda }$ model is proposed to control the bits per frame even more precisely. The experimental results demonstrate that the proposed $\boldsymbol {\lambda }$ -domain rate control algorithm can bring both more precise bitrate accuracy and better R-D performance compared with the previous rate control algorithms for HEVC scalable extension.

Adaptive Bit Allocation for 3D Video Coding

In the multi-view video plus depth 3D video coding, texture image and depth map are coded jointly. The texture image is utilized for displaying and synthesizing the virtual view as reference image. The depth map provides the scene geometry information and is utilized to synthesize the virtual view at the terminal through Depth-Image Based Rendering technique. The distortion of the compressed texture image and depth map will be propagated to the synthesized virtual view. Besides the coding efficiency of texture image and depth map, bit allocation between texture image and depth map also has a great effect on the synthesized virtual view quality. Several methods are proposed for bit allocation between texture image and depth map, but most of them attempt to allocate a fixed target bitrate based on virtual view distortion model to achieve optimal synthesized virtual view quality, and the modeling process brings extra complexity. In practical application, the video sequence has different contents and fixed bit ratio cannot achieve optimal performance. In this paper, we propose an adaptive bit allocation algorithm for 3D video coding. First, we present a model to estimate the synthesized virtual view distortion, and then adjust the bit ratio between adjacent views and between texture image and depth map at Group of Picture level based on the virtual view quality fluctuation. We adjust the bit ratio to achieve the optimal virtual view quality for different video contents. Experimental results demonstrate that the proposed algorithm can optimally allocate bits to achieve optimal virtual view quality under different target bitrates and for different video contents, and the computational complexity of the proposed algorithm is extremely low.

Pyramid coding based rate control for variable bit rate video streaming

Multi-pass encoding is preferred over single-pass encoding for applications such as television broadcasting and video on demand to obtain a consistent visual quality media. This study presents a novel pyramid coding based two-pass rate control scheme for variable bit rate video streaming. The proposed algorithm uses the statistics collected in the first pass to derive an optimal quantisation parameter for encoding the frames in the second pass. Simple linear estimation models are employed along with Gaussian filtering to update the frame quantisation parameter values in an adaptive manner, resulting in a smoother variation among these values and a better visual quality. The experimental results demonstrate that the proposed rate control scheme exhibits a better performance in terms of the peak signal-to-noise ratio and consistent perceptual visual quality in comparison with the existing rate control scheme in the joint model reference software while achieving the target bit rate.

Frame-level bit allocation for hierarchical coding of H.265/HEVC considering dependent rate-distortion characteristics

Rate control plays an important role in video coding for rectifying the coded bit stream to meet the transmission bandwidth, which is related to two parts of bit allocation and quantization parameter acquirement. Considering that the bit allocation is a critical step due to its effect on the subsequent coding operation and rate-distortion performance, therefore in this paper an accurate H.265/HEVC frame-level bit allocation algorithm is proposed for higher coding efficiency. Concretely the feature regarding the inter-frame dependency is firstly analyzed based on the theoretical derivation. Then the hierarchically dependent characteristics are extracted and utilized to establish the bit allocation model. Experimental results show that the proposed method can guarantee a good consistency between the target bits and coded bits, where a PSNR improvement of about 0. 131 dB can be observed compared with the original H.265/HEVC bit allocation while keeping the same bit rate.

Rate control for HEVC based on spatio-temporal context and motion complexity

Rate control plays a crucial role in video coding. Existing rate control methods for high efficiency video coding standard (HEVC) hardly take advantage of spatio-temporal context information when updating model parameters, resulting in inaccurate computation of the Lagrange multiplier and quantization parameter (QP). Meanwhile, these methods fail to consider the motion complexity of a basic unit (BU). Therefore, a large mismatch may exist between the allocated bits and actually encoded bits. In this paper, we propose an effective rate control scheme for HEVC at the BU layer to exploit both the spatio-temporal context and motion complexity. Firstly, the actually used Lagrange multiplier and generated bits of the highly correlated coded BUs in the spatio-temporal context are carefully weighted to update the model parameters. Secondly, the allocated bits for a BU are adjusted based on its motion complexity. Thus, an improved Lagrange multiplier is more accurate in minimizing the difference between the target bits and actually generated bits. Experimental results show that our proposed method outperforms the current scheme in HM with negligible complexity increase.

Low-Complexity and Context-Aware Estimation of Spatial and Temporal Activity Parameters for Automotive Camera Rate Control

Rate control in video compression adjusts the encoding parameters to reach a certain target bitrate for the encoded video. State-of-the-art rate controllers for hybrid video coding typically employ content-dependent video bitrate models and video quality metrics (VQMs). To capture the content characteristics, temporal and spatial video activity measures are determined from the raw video using computationally complex algorithms that require access to the uncompressed source video. In automotive deployments, however, full access to the uncompressed source video and the internal functions of video encoders is typically not possible. As a remedy, in this paper, we present a low-complexity approach to estimate the temporal activity (TA) and spatial activity (SA) measures for videos that are captured by a front-facing camera of a vehicle, based on the context information of the vehicle. To this end, we exploit information about the dynamics of the vehicle and other vehicles in the field-of-view of the front-facing camera. We apply the estimated TA and SA values to a video bitrate model and an objective VQM and use these models to solve the rate control problem to determine the optimal encoding settings for given bitrate constraints. The proposed low-complexity solution offers a similar accuracy in achieving rate constraints and similar perceptual quality characteristics as a solution that uses the computed TA and SA values, with the advantage that no access to the uncompressed source video stream or the internal functions of the video encoder is required.

An Efficient Frame-Level Rate Control Algorithm for High Efficiency Video Coding

In video coding, the goal of rate control (RC) is not only to avoid the undesirable fluctuation in bit allocation, but also to provide a good visual perception. In this paper, a novel frame-level rate control algorithm for High Efficiency Video Coding (HEVC) is proposed. Firstly a model that reveals the relationship between bit per pixel (bpp), the bitrate of the intra frame and the bitrate of the subsequent inter frames in a group of pictures (GOP) is established, based on which the target bitrate of the first intra frame is well estimated. Then a novel frame-level bit allocation algorithm is developed, which provides a robust bit balancing scheme between the intra frame and the inter frames in a GOP to achieve the visual quality smoothness throughout the whole sequence. Our experimental results show that when compared to the RC scheme for HEVC encoder HM-16.0, the proposed algorithm can produce reconstructed frames with more consistent objective video quality. In addition, the objective visual quality of the reconstructed frames can be improved with less bitrate.

A Low-Power Video Recording System With Multiple Operation Modes for H.264 and Light-Weight Compression

An increasing demand for mobile video recording systems makes it important to reduce power consumption and to increase battery lifetime. The H.264/AVC compression is widely used for many video recording systems because of its high compression efficiency; however, the complex coding structure of H.264/AVC compression requires large power consumption. A light-weight video compression (LWC), based on discrete wavelet transform and set partitioning in hierarchical trees, consumes less power than H.264/AVC compression thanks to its relatively simple coding structure, although its compression efficiency is lower than that of H.264/AVC compression. This paper proposes a low-power video recording system that combines both the H.264/AVC encoder with high compression efficiency and LWC with low power consumption. The LWC is used to compress video data for temporal storage while the H.264/AVC encoder is used for permanent storage of data when some events are detected. For further power reduction, a down-sampling operation is utilized for permanent data storage. For an effective use of the two compressions with the down-sampling operation, an appropriate scheme is selected according to the proportion of long-term to short-term storage and the target bitrate. The proposed system reduces power consumption by up to 72.5% compared to that in a conventional video recording system.

Region-based bit allocation and rate control for depth video in HEVC

In this paper, we present a novel rate control method with optimized region-based bit allocation for depth video coding. First, a synthetic view distortion oriented segmentation method is proposed to divide depth video into different regions, including texture areas and smooth areas. Then, the expanded exponential distortion-rate (D-R) models and power quantization parameter-rate (QP-R) models are investigated to simulate rate-distortion (R-D) characteristics of different regions. Finally, an optimal bit allocation scheme is developed to adaptively allocate target bit with the division. Experimental results on various video sequences demonstrate that the proposed algorithm achieves excellent R-D efficiency and bit rate accuracy compared with benchmark algorithms.