Optimized particle swarm optimization for faster and accurate video compression
The motion of objects in a video from one frame to another must be estimated quickly to speed up the video compression process. However, this should not deteriorate the visual appearance of the contents beyond the appropriate scope. This paper proposes improvisation of the fundamental Particle Swarm...
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| Veröffentlicht in: | Multimedia tools and applications Jg. 81; H. 16; S. 23289 - 23310 |
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| Sprache: | Englisch |
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01.07.2022
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| Abstract | The motion of objects in a video from one frame to another must be estimated quickly to speed up the video compression process. However, this should not deteriorate the visual appearance of the contents beyond the appropriate scope. This paper proposes improvisation of the fundamental Particle Swarm Optimization (PSO), known as Optimized PSO, to balance video compression quality and speed. The inertia portion of the particle velocity is modified dynamically to address the quality needed and broadly defines the movement to the global best place. To make the process quicker, additional stopping parameters, including predefined block distortion measurement, i.e., thresholds and the early identification of static macroblocks, are used to eradicate the movement estimation process for non-moving macroblocks. A small diamond search pattern is also implemented to investigate the impact of search patterns on optimizing the particulate swarm on the motion estimation process. The detailed simulations performed on different videos have proved that the proposed Optimized PSO versions for the block matching algorithm surpass several current modular block matching algorithms. It also produces even better estimation precision and speed than the possible particle swarm optimization-based motion estimation. The proposed versions of PSO-BMA referred to as Optimized PSOs have gained a speed up to 90-95% than that of FS with an acceptable compromise between the qualities of the reconstructed image. |
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| AbstractList | The motion of objects in a video from one frame to another must be estimated quickly to speed up the video compression process. However, this should not deteriorate the visual appearance of the contents beyond the appropriate scope. This paper proposes improvisation of the fundamental Particle Swarm Optimization (PSO), known as Optimized PSO, to balance video compression quality and speed. The inertia portion of the particle velocity is modified dynamically to address the quality needed and broadly defines the movement to the global best place. To make the process quicker, additional stopping parameters, including predefined block distortion measurement, i.e., thresholds and the early identification of static macroblocks, are used to eradicate the movement estimation process for non-moving macroblocks. A small diamond search pattern is also implemented to investigate the impact of search patterns on optimizing the particulate swarm on the motion estimation process. The detailed simulations performed on different videos have proved that the proposed Optimized PSO versions for the block matching algorithm surpass several current modular block matching algorithms. It also produces even better estimation precision and speed than the possible particle swarm optimization-based motion estimation. The proposed versions of PSO-BMA referred to as Optimized PSOs have gained a speed up to 90-95% than that of FS with an acceptable compromise between the qualities of the reconstructed image. |
| Author | Choudhury, Hussain Ahmed Sinha, Nidul Saikia, Monjul |
| Author_xml | – sequence: 1 givenname: Monjul orcidid: 0000-0002-7316-0254 surname: Saikia fullname: Saikia, Monjul email: monjuls@gmail.com organization: Department of Computer Science and Engineering, North Eastern Regional Institute of Science and Technology – sequence: 2 givenname: Hussain Ahmed surname: Choudhury fullname: Choudhury, Hussain Ahmed organization: Department of CSE, VIT Andhra Pradesh – sequence: 3 givenname: Nidul surname: Sinha fullname: Sinha, Nidul organization: Department of Electrical Engineering, National Institute of Technology, Silchar |
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| Cites_doi | 10.1016/j.image.2011.06.002 10.1016/j.asoc.2012.09.020 10.1109/TCSVT.2002.1003474 10.1049/el:19900183 10.1109/TMM.2004.840609 10.1109/83.821744 10.1109/76.313138 10.1109/76.499840 10.1109/TCSVT.2002.806815 10.1093/ietfec/e90-a.4.764 10.1109/TEVC.2004.826069 10.1109/76.510936 10.1016/j.sigpro.2008.12.012 10.1109/26.57512 10.1016/j.image.2015.09.010 10.1109/30.713175 10.1109/ICESS.2008.35 10.1109/ICICES.2014.7033946 10.1109/ICNN.1995.488968 10.1007/978-81-322-2464-8_12 10.1007/s00521-019-04635-6 10.1016/j.image.2008.08.004 10.1109/76.260203 10.1016/j.ins.2012.02.014 10.1049/ip-i-2.1990.0029 10.3233/JIFS-181790 10.1016/j.engappai.2013.04.003 10.1109/TCOM.1981.1094950 10.1109/TIP.2002.806251 |
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| DOI | 10.1007/s11042-022-12522-x |
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| Keywords | MAD Cost function Motion estimation Block matching algorithm Particle swarm optimization |
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| Snippet | The motion of objects in a video from one frame to another must be estimated quickly to speed up the video compression process. However, this should not... |
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| SubjectTerms | Algorithms Computer Communication Networks Computer Science Data Structures and Information Theory Diamonds Elementary particles Image reconstruction Matching Motion simulation Multimedia Information Systems Object motion Optimization Particle swarm optimization Process parameters Special Purpose and Application-Based Systems Video compression |
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| Title | Optimized particle swarm optimization for faster and accurate video compression |
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| Volume | 81 |
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