Mobile devices performing video coding and streaming over wireless and pervasive communication networks are limited in energy supply. To prolong the operational lifetime of these devices, an embedded video encoding system should be able to adjust its computational complexity and energy consumption as demanded by the situation and its environment. To analyze, control, and optimize the rate-distortion (R-D) behavior of the wireless video communication system under the energy constraint, we develop a power-rate-distortion (P-R-D) analysis framework, which extends the traditional R-D analysis by including another dimension, the power consumption. Specifically, in this paper, we analyze the encoding mechanism of typical video coding systems, and develop a parametric video encoding architecture which is fully scalable in computational complexity. Using dynamic voltage scaling (DVS), an energy consumption management technology recently developed in CMOS circuits design, the complexity scalability can be translated into the energy consumption scalability of the video encoder. We investigate the R-D behavior of the complexity control parameters and establish an analytic P-R-D model. Both theoretically and experimentally, we show that, using this P-R-D model, the video coding system is able to automatically adjust its complexity control parameters to match the available energy supply of the mobile device while maximizing the picture quality. The P-R-D model provides a theoretical guideline for system design and performance optimization in mobile video communication under energy constraints.

Power-rate-distortion analysis for wireless video communication under energy constraints

Motion Estimation (ME) for video coding has taken an entirely different direction with the emergence of zonal algorithms. These algorithms made it possible to significantly reduce, if not almost eliminate, the tremendous computational overhead of motion estimation that was incurred in a video encoding system, while having little if any loss in quality. In this paper we further improve on these algorithms with the introduction of the Enhanced Predictive Zonal Search Algorithm (EPZS). By considering an additional set of predictors, improving the thresholding process, and simplifying the search pattern employed by these algorithms, we not only manage in achieving better output quality, but also reduce complexity of the motion estimation process even further. Our algorithm was compared with the algorithms accepted in the Optimization Model 1.0 of MPEG-4, and our simulations prove its outright superiority versus the existing algorithms. Furthermore we present a 3-Dimensional implementation of EPZS, which can be easily applied in the case of multiple frame motion estimation (ITU H.263++ and H.26L).

Enhanced predictive zonal search for single and multiple frame motion estimation

Motion estimation (ME) is an important part of any video encoding system since it could significantly affect the output quality of an encoded sequence. Unfortunately, this feature requires a significant part of the encoding time especially when using the straightforward full search (FS) algorithm. We propose two techniques, the generalized motion vector (MV) predictor and the adaptive threshold calculation, that can be used to significantly improve the performance of many existing fast ME algorithms. In particular, we apply them to create two new algorithms, named advanced predictive diamond zonal search and predictive MV field adaptive search technique, respectively, which can considerably reduce, if not essentially remove, the computational cost of ME at the encoder, while at the same time give similar, and in many cases better, visual quality with the brute force full search algorithm. The proposed algorithms mainly rely upon very robust and reliable predictive techniques and early termination criteria with parameters adapted to the local characteristics combined with the zonal based patterns. Our experiments verify the considerable superiority of the proposed algorithms versus the performance of possibly all other known fast algorithms, and FS.

Highly efficient predictive zonal algorithms for fast block-matching motion estimation

Fast integer-pel and fractional-pel motion estimation for H.264/AVC

Fast block motion estimation normally consists of low-resolution coarse search and the following fine-resolution inner search. Most motion estimation algorithms developed attempt to speed up the coarse search without considering accelerating the focused inner search. On top of the hexagonal search method recently developed, an enhanced hexagonal search algorithm is proposed to further improve the performance in terms of reducing number of search points and distortion, where a novel fast inner search is employed by exploiting the distortion information of the evaluated points. Our experimental results substantially justify the merits of the proposed algorithm.

/pdf/enhanced-hexagonal-search-for-fast-block-motion-estimation-1sntiozao2.pdf

Enhanced hexagonal search for fast block motion estimation

Motion Estimation (ME) is an important part of most video encoding systems, since it could significantly affect the output quality of an encoded sequence. Unfortunately this feature requires a significant part of the encoding time especially when using the straightforward Full Search (FS) algorithm. In this paper a new algorithm is presented named as the Predictive Motion Vector Field Adaptive Search Technique (PMVFAST), which significantly outperforms most if not all other previously proposed algorithms in terms of Speed Up performance. In addition, the output quality of the encoded sequence in terms of PSNR is similar to that of the Full Search algorithm. The proposed algorithm relies mainly upon very robust and reliable predictive techniques and early termination criteria, which make use of parameters adapted to the local characteristics of a frame. Our experiments verify the superiority of the proposed algorithm, not only versus several other well-known fast algorithms, but also in many cases versus even the Full Search algorithm.

Predictive motion vector field adaptive search technique (PMVFAST): enhancing block-based motion estimation

Predictive motion vector field adaptive search technique (PMVFAST) - enhancing block based motion estimation

A device or method for video compression uses a technique in which changes in the image are encoded by motions of block of the image and signals indicating evolutions in the block. To determine the motions of the blocks of a each frame, a search is performed for a similar block of a previous frame based on points of the previous frame which are arranged in successive diamond shaped zones. The diamond shaped zones may be centred on the position of the block in previous frame, or one or more predicted motions of the block. The method terminates according to criteria defined using thresholds.

Device, method and digital video encoder for block-matching motion estimation

Zonal based motion estimation algorithms have been gaining in popularity in video coding. This is due to their superior performance and reduced complexity versus other conventional algorithms. In this paper we propose a further improvement on these algorithms named the Advanced Predictive Diamond Zonal Search (APDZS). The proposed algorithm introduces the concepts of multiple initial predictor candidates and adaptive thresholding, and manages to significantly improve the reliability and performance of the estimation. Extensive simulation results demonstrate that the performance of this algorithm is equivalent in terms of PSNR, to that of the brute force full search algorithm even for the most complicated sequences, with almost negligible complexity.

New results on zonal based motion estimation algorithms-advanced predictive diamond zonal search

Driven by the rapidly increasing demand for audio-visual applications, digital video compression technology has become a mature field, offering several available products based on both hardware and software implementations. Taking advantage of spatial, temporal, and statistical redundancies in video data, a video compression system aims to maximize the compression ratio while maintaining a high picture quality. Despite the tremendous progress in this area, video compression remains a challenging research problem due to its computational requirements and also because of the need for higher picture quality at lower data rates. Designing efficient coding algorithms continues to be a prolific area of research. For circumvent the computational requirement, researchers has resorted to parallel processing with a variety of approaches using dedicated parallel VLSI architectures as well as software on general-purpose available multiprocessor systems. Despite the availability of fast single processors, parallel processing helps to explore advanced algorithms and to build more sophisticated systems. This paper presents an overview of the recent research in video compression using parallel processing. The paper provides a discussion of the basic compression techniques, existing video coding standards, and various parallelization approaches. Since video compression is multi-step in nature using various algorithms, parallel processing can be exploited at an individual algorithm or at a complete system level. The paper covers a broad spectrum of such approaches, outlining the basic philosophy of each approach and providing examples. We contrast these approaches when possible, highlight their pros and cons, and suggest future research directions. While the emphasis of this paper is on software-based methods, a significant discussion of hardware and VLSI is also included.

/pdf/video-compression-with-parallel-processing-2y3katbvpl.pdf

M.L. Liou

Papers

Predictive motion vector field adaptive search technique (PMVFAST): enhancing block-based motion estimation

Predictive motion vector field adaptive search technique (PMVFAST) - enhancing block based motion estimation

Device, method and digital video encoder for block-matching motion estimation

New results on zonal based motion estimation algorithms-advanced predictive diamond zonal search

Video compression with parallel processing