Region-of-interest based rate control scheme for high efficiency video coding

International audienceIn this paper, we propose a new rate control scheme designed for the newest high efficiency video coding (HEVC) standard, and aimed at enhancing the quality of regions of interest (ROI). Our approach allocates a higher bit rate to the region of interest while keeping the global bit rate close to the assigned target value. This algorithm is developed for a videoconferencing system, where the ROIs (typically, faces) are automatically detected and each coding unit is classified in a region of the interest map. This map is given as input to the rate control algorithm and the bit allocation is made accordingly. Experimental results show that the proposed scheme achieves accurate target bit rates and provides an improvement in the region of interest quality, both in objective metrics and based on subjective quality evaluation

Rate control for HEVC intra-coding based on piecewise linear approximations

This paper proposes a rate control (RC) algorithm for intra-coded sequences (I-frames) within the context of block-based predictive transform coding (PTC) that employs piecewise linear approximations of the rate-distortion (RD) curve of each frame. Specifically, it employs information about the rate (R) and distortion (D) of already compressed blocks within the current frame to linearly approximate the slope of the corresponding RD curve. The proposed algorithm is implemented in the High-Efficiency Video Coding (HEVC) standard and compared with the current HEVC RC algorithm, which is based on a trained rate lambda (R-λ) model. Evaluations on a variety of intra-coded sequences show that the proposed RC algorithm not only attains the overall target bit rate more accurately than the current RC algorithm but is also capable of encoding each I-frame at a more constant bit rate according to the overall bit budget, thus avoiding high bit rate fluctuations across the sequence

EFFICIENT QUANTIZATION PARAMETER ESTIMATION IN HEVC BASED ON ρ-DOMAIN

International audienceThis paper proposes a quantization parameter estimation algorithm for HEVC CTU rate control. Several methods were proposed, mostly based on Lagrangian optimization combined with Laplacian distribution for transformed coeffi-cients. These methods are accurate but increase the encoder complexity. This paper provides an innovative reduced com-plexity algorithm based on a ρ-domain rate model. Indeed, for each CTU, the algorithm predicts encoding parameters based on co-located CTU. By combining it with Laplacian distri-bution for transformed coefficients, we obtain the dead-zone boundary for quantization and the related quantization pa-rameter. Experiments in the HEVC HM Reference Software show a good accuracy with only a 3% average bitrate error and no PSNR deterioration for random-access configuration

Overview of the Low Complexity Enhancement Video Coding (LCEVC) Standard

The Low Complexity Enhancement Video Coding (LCEVC) specification is a recent standard approved by the ISO/IEC JTC 1/SC 29/WG04 (MPEG) Video Coding. The main goal of LCEVC is to provide a standalone toolset for the enhancement of any other existing codec. It works on top of other coding schemes, resulting in a multi-layer video coding technology, but unlike existing scalable video codecs, adds enhancement layers completely independent from the base video. The LCEVC technology takes as input the decoded video at lower resolution and adds up to two enhancement sub-layers of residuals encoded with specialized low-complexity coding tools, such as simple temporal prediction, frequency transform, quantization, and entropy encoding. This paper provides an overview of the main features of the LCEVC standard: high compression efficiency, low complexity, minimized requirements of memory and processing power

Rate-Distortion Modeling for Bit Rate Constrained Point Cloud Compression

As being one of the main representation formats of 3D real world and well-suited for virtual reality and augmented reality applications, point clouds have gained a lot of popularity. In order to reduce the huge amount of data, a considerable amount of research on point cloud compression has been done. However, given a target bit rate, how to properly choose the color and geometry quantization parameters for compressing point clouds is still an open issue. In this paper, we propose a rate-distortion model based quantization parameter selection scheme for bit rate constrained point cloud compression. Firstly, to overcome the measurement uncertainty in evaluating the distortion of the point clouds, we propose a unified model to combine the geometry distortion and color distortion. In this model, we take into account the correlation between geometry and color variables of point clouds and derive a dimensionless quantity to represent the overall quality degradation. Then, we derive the relationships of overall distortion and bit rate with the quantization parameters. Finally, we formulate the bit rate constrained point cloud compression as a constrained minimization problem using the derived polynomial models and deduce the solution via an iterative numerical method. Experimental results show that the proposed algorithm can achieve optimal decoded point cloud quality at various target bit rates, and substantially outperform the video-rate-distortion model based point cloud compression scheme.Comment: Accepted to IEEE Transactions on Circuits and Systems for Video Technolog

Towards visualization and searching :a dual-purpose video coding approach

In modern video applications, the role of the decoded video is much more than filling a screen for visualization. To offer powerful video-enabled applications, it is increasingly critical not only to visualize the decoded video but also to provide efficient searching capabilities for similar content. Video surveillance and personal communication applications are critical examples of these dual visualization and searching requirements. However, current video coding solutions are strongly biased towards the visualization needs. In this context, the goal of this work is to propose a dual-purpose video coding solution targeting both visualization and searching needs by adopting a hybrid coding framework where the usual pixel-based coding approach is combined with a novel feature-based coding approach. In this novel dual-purpose video coding solution, some frames are coded using a set of keypoint matches, which not only allow decoding for visualization, but also provide the decoder valuable feature-related information, extracted at the encoder from the original frames, instrumental for efficient searching. The proposed solution is based on a flexible joint Lagrangian optimization framework where pixel-based and feature-based processing are combined to find the most appropriate trade-off between the visualization and searching performances. Extensive experimental results for the assessment of the proposed dual-purpose video coding solution under meaningful test conditions are presented. The results show the flexibility of the proposed coding solution to achieve different optimization trade-offs, notably competitive performance regarding the state-of-the-art HEVC standard both in terms of visualization and searching performance.Em modernas aplicações de vídeo, o papel do vídeo decodificado é muito mais que simplesmente preencher uma tela para visualização. Para oferecer aplicações mais poderosas por meio de sinais de vídeo,é cada vez mais crítico não apenas considerar a qualidade do conteúdo objetivando sua visualização, mas também possibilitar meios de realizar busca por conteúdos semelhantes. Requisitos de visualização e de busca são considerados, por exemplo, em modernas aplicações de vídeo vigilância e comunicações pessoais. No entanto, as atuais soluções de codificação de vídeo são fortemente voltadas aos requisitos de visualização. Nesse contexto, o objetivo deste trabalho é propor uma solução de codificação de vídeo de propósito duplo, objetivando tanto requisitos de visualização quanto de busca. Para isso, é proposto um arcabouço de codificação em que a abordagem usual de codificação de pixels é combinada com uma nova abordagem de codificação baseada em features visuais. Nessa solução, alguns quadros são codificados usando um conjunto de pares de keypoints casados, possibilitando não apenas visualização, mas também provendo ao decodificador valiosas informações de features visuais, extraídas no codificador a partir do conteúdo original, que são instrumentais em aplicações de busca. A solução proposta emprega um esquema flexível de otimização Lagrangiana onde o processamento baseado em pixel é combinado com o processamento baseado em features visuais objetivando encontrar um compromisso adequado entre os desempenhos de visualização e de busca. Os resultados experimentais mostram a flexibilidade da solução proposta em alcançar diferentes compromissos de otimização, nomeadamente desempenho competitivo em relação ao padrão HEVC tanto em termos de visualização quanto de busca