NDLI: Multi-objective genetic algorithm on hexagonal search for fast motion estimation

Content Provider	IET Digital Library
Author	Palaniraj, Palanivel Sakthivel, Ganesan
Abstract	Motion estimation (ME) is a process of correlating the frames by pointing the blocks in the candidate frame similar to those in the previous frame. Hexagonal Search (HS) reduces 10–15% search points over Diamond Search (DS) with negligible Peak Signal to Noise Ratio (PSNR) loss. Adapting an optimization will achieve a massive improvement on the search process. The proposed HS-GA method combines the HS with genetic algorithm (GA) to optimize ME. The HS-GA method reduces 72% on average search points pre block (ASPB) with PSNR loss of 2.5 dB and single generation. If the GA is executed with 10 generations the PSNR loss is reduced to 0.48 dB, but ASPB drastically increase to ∼316%. The proposed work aims at multi objective on selection of better chromosomes and on control of generations to avoid the unnecessary generations to improve the GA. This process is named HSIGA(HS with Intelligent GA). The proposed HSIGA adapts five intelligent techniques like Histogram to decide new generations, Region based chromosome selection, Mutation on inner search gene, second rank valley point stopping criteria and interlaced HS to improve search process with negligible PSNR loss with in affordable search.
Starting Page	1892
Ending Page	1902
Page Count	11
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 11, Sep (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5918
Journal	IET Image Processing
Publisher Date	2019-07-02
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ASPB Average Search Points Pre-block Cellular Biophysics Computer Vision And Image Processing Technique Diamond Search Fast Motion Estimation Gene Selection Domain Genetic Algorithm Hexagonal Search HS-GA Method Inner Search Gene Motion Estimation Multiobjective Genetic Algorithm Negligible PSNR Loss Optical, Image And Video Signal Processing Optimisation Optimisation Technique Poisson Distribution Poisson-distributed Random Genes Probability Region-based Chromosome Selection Search Problem Search Process Second-rank Valley Point Stopping Criteria Statistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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