A Survey on Block Matching Algorithms for Video Coding

Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades, hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality

Performance Analysis of Hexagon-Diamond Search Algorithm for Motion Estimation using MATLAB

To achieve a high compression ratio in coding video data, a method known as Motion Estimation (ME) is often applied to reduce the temporal redundancy between successive frames of a video sequence. One of ME techniques, known as Block Matching Algorithm (BMA), has been widely used in various video coding standards. In recent years, many of these BMAs have been developed with similar intention of reducing the computational costs while at the same time maintaining the video signal quality. In this paper, an algorithm called Hexagon-Diamond Search (HDS) is proposed for ME where the algorithm and several fast BMAs, namely Three Step Search (TSS), New Three Step Search (NTSS), Four Step Search (4SS) as well as Diamond Search (DS), are first selected to be implemented onto various type of standard test video sequence using MATLAB before their performances are compared and analyzed in terms of peak signal-to-noise ratio (PSNR), number of search points needed as well as their computational complexity. Simulation results demonstrate that HDS algorithm has speed up other algorithm’s computational work up to 56% while at the same time maintains close performance in terms of PSNR to others

MPEG-4 Software Video Encoding

A Thesis submitted in fulfillment of the requirements of the degree of doctor of Philosophy in the University of LondonThis thesis presents a software model that allows a parallel decomposition of the MPEG-4 video encoder onto shared memory architectures, in order to reduce its total video encoding time. Since a video sequence consists of video objects each of which is likely to have different encoding requirements, the model incorporates a scheduler which (a) always selects the most appropriate video object for encoding and, (b) employs a mechanism for dynamically allocating video objects allocation onto the system processors, based on video object size information. Further spatial video object parallelism is exploited by applying the single program multiple data (SPMD) paradigm within the different modules of the MPEG-4 video encoder. Due to the fact that not all macroblocks have the same processing requirements, the model also introduces a data partition scheme that generates tiles with identical processing requirements. Since, macroblock data dependencies preclude data parallelism at the shape encoder the model also introduces a new mechanism that allows parallelism using a circular pipeline macroblock technique The encoding time depends partly on an encoder’s computational complexity. This thesis also addresses the problem of the motion estimation, as its complexity has a significant impact on the encoder’s complexity. In particular, two fast motion estimation algorithms have been developed for the model which reduce the computational complexity significantly. The thesis includes experimental results on a four processor shared memory platform, Origin200

Adaptive search center non-linear three step search

This paper presents a new motion estimation algorithm using an adaptive search center predicted from its adjacent blocks, and a non-linear center biased search point pattern. It does not have the problem of being trapped by local minimum, and is characterized by finding the majority motion vector in one step. When compared with six other block-based search algorithms including the full-search and three-step-search, the new algorithm has an average PSNR very close to that of full-search, yet an average search time faster than the three-step-search.published_or_final_versio

A Complexity and Quality Evaluation of Block Based Motion Estimation Algorithms

Motion estimation is a method, by which temporal redundancies are reduced, which is an important aspect of video compression algorithms. In this paper we present a comparison among some of the well-known block based motion estimation algorithms. A performance evaluation of these algorithms is proposed to decide the best algorithm from the point of view of complexity and quality for noise-free video sequences and also for noisy video sequences.