A Novel Video Compression Algorithm Using Wavelet Transform and neural network

Videos are made up of a temporal sequence of frames and are projected at a proper rate to create the illusion of motion. This means that there exists a high correlation between adjacent temporal frames so that when projected at a proper rate, smooth motion is seen. Correlation between adjacent tempo...

Full description

Bibliographic Details
Main Authors: Mohammad Rahmanian, Ahmad Hatam, Mohammad Ali Shafieeian
Format: Article
Language:English
Published: Najafabad Branch, Islamic Azad University 2016-01-01
Series:Journal of Intelligent Procedures in Electrical Technology
Subjects:
Online Access:http://jipet.iaun.ac.ir/article_13223_68d2d54707ed8b6788b4b1b8d615b048.pdf
id doaj-9b8886b8ed9042ddba4c4cf84e8ff628
record_format Article
spelling doaj-9b8886b8ed9042ddba4c4cf84e8ff6282020-11-24T23:56:14ZengNajafabad Branch, Islamic Azad UniversityJournal of Intelligent Procedures in Electrical Technology2322-38712345-55942016-01-01725314A Novel Video Compression Algorithm Using Wavelet Transform and neural networkMohammad Rahmanian0Ahmad Hatam1Mohammad Ali Shafieeian2Boushehr Branch, Islamic Azad UniversityHormozgan UniversityShiraz UniversityVideos are made up of a temporal sequence of frames and are projected at a proper rate to create the illusion of motion. This means that there exists a high correlation between adjacent temporal frames so that when projected at a proper rate, smooth motion is seen. Correlation between adjacent temporal frames is called interframe correlation. In order to decode compressed video bit stream uniformly by various platforms and devices, the bit stream format must be predefined. Thus, there must be a standard for a video compressor, which will enable all standard-compliant compressed video data to be decoded anywhere. The goal is to propose a new video compression algorithm based on wavelet transform and neural networks. Using wavelet transform leads to factorization in temporal as well as spatial domain. The goal in this paper is to achieve a compression algorithm which would be faster and has more compression ratio. Neural networks are used for prediction which is one of the most important functions in any video compression scheme. Furthermore, the proposed algorithm is compared with MPEG standard. Simulation results show the befits of using wavelet transform which reveal that the proposed algorithm is faster and has better performance in some aspects compared to MPEG standard. The video which obtained from proposed algorithm has acceptable in human visual and since it needs less than space for storing, it is suitable for portable devices.http://jipet.iaun.ac.ir/article_13223_68d2d54707ed8b6788b4b1b8d615b048.pdfvideo compressionmotion compensationmotion estimationvideo encoder and decoderMPEG standard
collection DOAJ
language English
format Article
sources DOAJ
author Mohammad Rahmanian
Ahmad Hatam
Mohammad Ali Shafieeian
spellingShingle Mohammad Rahmanian
Ahmad Hatam
Mohammad Ali Shafieeian
A Novel Video Compression Algorithm Using Wavelet Transform and neural network
Journal of Intelligent Procedures in Electrical Technology
video compression
motion compensation
motion estimation
video encoder and decoder
MPEG standard
author_facet Mohammad Rahmanian
Ahmad Hatam
Mohammad Ali Shafieeian
author_sort Mohammad Rahmanian
title A Novel Video Compression Algorithm Using Wavelet Transform and neural network
title_short A Novel Video Compression Algorithm Using Wavelet Transform and neural network
title_full A Novel Video Compression Algorithm Using Wavelet Transform and neural network
title_fullStr A Novel Video Compression Algorithm Using Wavelet Transform and neural network
title_full_unstemmed A Novel Video Compression Algorithm Using Wavelet Transform and neural network
title_sort novel video compression algorithm using wavelet transform and neural network
publisher Najafabad Branch, Islamic Azad University
series Journal of Intelligent Procedures in Electrical Technology
issn 2322-3871
2345-5594
publishDate 2016-01-01
description Videos are made up of a temporal sequence of frames and are projected at a proper rate to create the illusion of motion. This means that there exists a high correlation between adjacent temporal frames so that when projected at a proper rate, smooth motion is seen. Correlation between adjacent temporal frames is called interframe correlation. In order to decode compressed video bit stream uniformly by various platforms and devices, the bit stream format must be predefined. Thus, there must be a standard for a video compressor, which will enable all standard-compliant compressed video data to be decoded anywhere. The goal is to propose a new video compression algorithm based on wavelet transform and neural networks. Using wavelet transform leads to factorization in temporal as well as spatial domain. The goal in this paper is to achieve a compression algorithm which would be faster and has more compression ratio. Neural networks are used for prediction which is one of the most important functions in any video compression scheme. Furthermore, the proposed algorithm is compared with MPEG standard. Simulation results show the befits of using wavelet transform which reveal that the proposed algorithm is faster and has better performance in some aspects compared to MPEG standard. The video which obtained from proposed algorithm has acceptable in human visual and since it needs less than space for storing, it is suitable for portable devices.
topic video compression
motion compensation
motion estimation
video encoder and decoder
MPEG standard
url http://jipet.iaun.ac.ir/article_13223_68d2d54707ed8b6788b4b1b8d615b048.pdf
work_keys_str_mv AT mohammadrahmanian anovelvideocompressionalgorithmusingwavelettransformandneuralnetwork
AT ahmadhatam anovelvideocompressionalgorithmusingwavelettransformandneuralnetwork
AT mohammadalishafieeian anovelvideocompressionalgorithmusingwavelettransformandneuralnetwork
AT mohammadrahmanian novelvideocompressionalgorithmusingwavelettransformandneuralnetwork
AT ahmadhatam novelvideocompressionalgorithmusingwavelettransformandneuralnetwork
AT mohammadalishafieeian novelvideocompressionalgorithmusingwavelettransformandneuralnetwork
_version_ 1725458971727233024