Research Article
Variable Block Based Motion Estimation Using Hexagon Diamond Full Search Algorithm (HDFSA) via Block Subtraction Technique
@INPROCEEDINGS{10.1007/978-3-319-11629-7_12, author={Ranjit Singh and Jitvinder Singh and Lim Chuan}, title={Variable Block Based Motion Estimation Using Hexagon Diamond Full Search Algorithm (HDFSA) via Block Subtraction Technique}, proceedings={Signal Processing and Information Technology. Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers}, proceedings_a={SPIT}, year={2014}, month={11}, keywords={Variable Block Based Motion Estimation Hexagon Diamond Block Subtraction Technique}, doi={10.1007/978-3-319-11629-7_12} }- Ranjit Singh
Jitvinder Singh
Lim Chuan
Year: 2014
Variable Block Based Motion Estimation Using Hexagon Diamond Full Search Algorithm (HDFSA) via Block Subtraction Technique
SPIT
Springer
DOI: 10.1007/978-3-319-11629-7_12
Abstract
Motion estimation is a process of estimating the pixels displacement between two successive frames. The most common motion estimation technique used in the modern world is the block based motion estimation method. There are two types of block based motion estimation method which is the fixed block size and variable block size. This paper introduces a newly developed variable block based Hexagon Diamond Full Search Algorithm which uses the variable block based motion estimation integrating the block subtraction technique. Three different variable block size of 16 × 16 pixels, 8 × 8 pixels and 4 × 4 pixels are introduced in this paper to estimate the different types of motions. In order to select a particular variable block size, the block subtraction technique is applied before the motion estimation process is conducted. The block subtraction technique is mainly used to select the variable block size based on the pixels changes that occur during the motion estimation process. In order to evaluate the performance of the variable block based Hexagon Diamond Full Search Algorithm, superior algorithms are used to compare its performance in terms of average Peak Signal to Noise Ratio (PSNR), average search points and elapsed processing time.
