A Study on Block Matching Algorithms and Gradient Based Method for Motion Estimation in Video Compression

Abstract

This paper mainly focuses on the classification of motion estimation algorithms used for video compression. Motion Estimation (ME) algorithms vary with respect to the a priori information and constraints they employ, as well as the method of computation they use to obtain the estimate. The classifications for ME algorithms are based on feature/region matching, gradient based methods, spatiotemporal energy methods, deterministic model based methods and stochastic model based methods. This paper focuses more on block matching algorithms (BMA), (used for motion estimation in video compression) which comes under feature/region matching and gradient based methods. In effect this paper compares 7 different types of block matching algorithms. In addition to the above comparisons a survey on the Shape-Adaptive Motion Estimation Algorithm for MPEG-4 Video Coding is also incorporated. The Shape-Adaptive Motion Estimation algorithm is based on the gradient based motion estimation method. It is one of the latest algorithm coming under gradient based method. The algorithms that are compared and discussed in this paper are widely accepted by the video compressing community. More over these algorithms are used for implementing various standards, which ranges from MPEG1 / H.261 to MPEG4 / H.263 and H.264/AVC. A very brief introduction to the entire flow of video compression is also presented in this paper.