An Efficient Mode Decision Algorithm Based on Dynamic Grouping and Adaptive Adjustment for H.264/AVC

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”The rate distortion optimization (RDO) enabled mode decision (MD) is one of the most important techniques introduced by H.264/AVC. By adopting the exhaustive calculation of rate distortion, the optimal MD enhances the video encoding quality. However, the computational complexity is significantly increased, which is a key challenge for real-time and low power consumption applications. This paper presents a new fast MD algorithm for highly efficient H.264/AVC encoder. The proposed algorithm employs a dynamic group of candidate inter/intra modes to reduce the computational cost. In order to minimize the performance loss incurred by improper mode selection for the previously encoded frames, an adaptive adjustment scheme based on the undulation of bitrate and PSNR is suggested. Experimental results show that the proposed algorithm reduces the encoding time by 35% on average, and the loss of PSNR is usually limited in 0.1 dB with less than 1% increase of bitrate

An Efficient Intra Prediction Algorithm for H.264/AVC High Profile

[[abstract]]A simple, highly efficient intra prediction algorithm to reduce the computational complexity of H.264/AVC High Profile is proposed. The algorithm combines two methods. The first method is a quant-based block-size selection decision that is based on the sum of the quantization AC coefficients among intra 8 × 8 mode predictions, combined with an error adjustment to select either intra 4 × 4 or intra 16 × 16 mode predictions. The second method is a novel direction-based prediction mode decision that is used to reduce the possible prediction modes for the rate-distortion (RD) optimization technique. Our experimental results demonstrate that the proposed algorithm reduces the encoding time by approximately 54% compared with that needed for an exhaustive search using the joint model reference software. The peak signal-to-noise ratio degradation is negligible, and the bit rate increment is minimal. Furthermore, the results show that our algorithm achieves a significant improvement in both computation performance and RD performance as compared with the existing algorithms.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]電子

An efficient fast mode decision algorithm for H.264/AVC intra/inter predictions

H.264/AVC is the newest video coding standard, which outperforms the former standards in video coding efficiency in terms of improved video quality and decreased bitrate. Variable block size based mode decision (MD) with rate distortion optimization (RDO) is one of the most impressive new techniques employed in H.264/AVC. However, the improvement on performance is achieved at the expense of significantly increased computational complexity, which is a key challenge for real-time applications. An efficient fast mode decision algorithm is then proposed in this paper. By exploiting the correlation between macroblocks and the statistical characteristics of sub-macroblock in MD, the video encoding time can be reduced 52.19% on average. Furthermore, the motion speed based adjustment scheme was introduced to minimize the degradation of performanc

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Lossless Intra Coding in HEVC with 3-tap Filters

This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC). A well-known previous pixel-by-pixel spatial prediction method uses only two neighboring pixels for prediction, based on the angular projection idea borrowed from block-based intra prediction in lossy coding. This paper explores a method which uses three neighboring pixels for prediction according to a two-dimensional correlation model, and the used neighbor pixels and prediction weights change depending on intra mode. To find the best prediction weights for each intra mode, a two-stage offline optimization algorithm is used and a number of implementation aspects are discussed to simplify the proposed prediction method. The proposed method is implemented in the HEVC reference software and experimental results show that the explored 3-tap filtering method can achieve an average 11.34% bitrate reduction over the default lossless intra coding in HEVC. The proposed method also decreases average decoding time by 12.7% while it increases average encoding time by 9.7%Comment: 10 pages, 7 figure

Coding local and global binary visual features extracted from video sequences

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks, while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the Bag-of-Visual-Word (BoVW) model. Several applications, including for example visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget, while attaining a target level of efficiency. In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can be conveniently adopted to support the Analyze-Then-Compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the Compress-Then-Analyze (CTA) paradigm. In this paper we experimentally compare ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.Comment: submitted to IEEE Transactions on Image Processin