scispace - formally typeset
Journal ArticleDOI

Efficient Parallel Framework for HEVC Motion Estimation on Many-Core Processors

Reads0
Chats0
TLDR
This paper analyzes the ME structure in HEVC and proposes a parallel framework to decouple ME for different partitions on many-core processors and achieves more than 30 and 40 times speedup for 1920 × 1080 and 2560 × 1600 video sequences, respectively.
Abstract
High Efficiency Video Coding (HEVC) provides superior coding efficiency than previous video coding standards at the cost of increasing encoding complexity. The complexity increase of motion estimation (ME) procedure is rather significant, especially when considering the complicated partitioning structure of HEVC. To fully exploit the coding efficiency brought by HEVC requires a huge amount of computations. In this paper, we analyze the ME structure in HEVC and propose a parallel framework to decouple ME for different partitions on many-core processors. Based on local parallel method (LPM), we first use the directed acyclic graph (DAG)-based order to parallelize coding tree units (CTUs) and adopt improved LPM (ILPM) within each CTU (DAGILPM), which exploits the CTU-level and prediction unit (PU)-level parallelism. Then, we find that there exist completely independent PUs (CIPUs) and partially independent PUs (PIPUs). When the degree of parallelism (DP) is smaller than the maximum DP of DAGILPM, we process the CIPUs and PIPUs, which further increases the DP. The data dependencies and coding efficiency stay the same as LPM. Experiments show that on a 64-core system, compared with serial execution, our proposed scheme achieves more than 30 and 40 times speedup for 1920 × 1080 and 2560 × 1600 video sequences, respectively.

read more

Citations
More filters
Journal ArticleDOI

Relationship between entropy and SNR changes in image enhancement

TL;DR: This approach is based on Hartley entropy, its estimation, and differentiation, and resulting gradient of entropy is estimated without knowledge of ideal images, and it is a subject of minimization.
Journal ArticleDOI

Point of interest mining with proper semantic annotation

TL;DR: Experimental results on two datasets of geo-tagged Flickr photos of two cities in California, USA have shown that the proposed method substantially outperforms existing approaches that are adapted to handle the problem.
Journal ArticleDOI

Hierarchical MK Splines: Algorithm and Applications to Data Fitting

TL;DR: Experimental results show that large-scale scattered data fitting can be easily achieved by the HMK splines algorithm and the reconstruction of nonuniform samples has a high accuracy.
Journal ArticleDOI

Triple Threshold Statistical Detection filter for removing high density random-valued impulse noise in images

TL;DR: A novel noise detection algorithm which satisfactorily detects noisy pixels in images corrupted by random-valued impulse noise of high levels up to 80% noise density and is able to outperform the existing methods in both the detection and filtering of random- valued impulse noise in images.
Journal ArticleDOI

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality

TL;DR: This paper develops a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs).
References
More filters
Book

The Design and Analysis of Computer Algorithms

TL;DR: This text introduces the basic data structures and programming techniques often used in efficient algorithms, and covers use of lists, push-down stacks, queues, trees, and graphs.
Journal ArticleDOI

Overview of the High Efficiency Video Coding (HEVC) Standard

TL;DR: The main goal of the HEVC standardization effort is to enable significantly improved compression performance relative to existing standards-in the range of 50% bit-rate reduction for equal perceptual video quality.
Journal ArticleDOI

Scope of validity of PSNR in image/video quality assessment

TL;DR: Experimental data are presented that clearly demonstrate the scope of application of peak signal-to-noise ratio (PSNR) as a video quality metric and it is shown that as long as the video content and the codec type are not changed, PSNR is a valid quality measure.
Related Papers (5)