{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T17:57:55Z","timestamp":1775584675774,"version":"3.50.1"},"reference-count":60,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T00:00:00Z","timestamp":1584662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, recognition and understanding and efficient processing of large amounts of video data. This research proposes a novel unified approach to lossy and lossless video frame compression, which is beneficial for the autonomous processing and enhanced representation of high-resolution video data in various domains. The proposed fast block matching motion estimation technique, namely mean predictive block matching, is based on the principle that general motion in any video frame is usually coherent. This coherent nature of the video frames dictates a high probability of a macroblock having the same direction of motion as the macroblocks surrounding it. The technique employs the partial distortion elimination algorithm to condense the exploration time, where partial summation of the matching distortion between the current macroblock and its contender ones will be used, when the matching distortion surpasses the current lowest error. Experimental results demonstrate the superiority of the proposed approach over state-of-the-art techniques, including the four step search, three step search, diamond search, and new three step search.<\/jats:p>","DOI":"10.3390\/rs12061004","type":"journal-article","created":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T11:42:11Z","timestamp":1584704531000},"page":"1004","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics"],"prefix":"10.3390","volume":"12","author":[{"given":"Zayneb","family":"Ahmed","sequence":"first","affiliation":[{"name":"Department of Mathematics, University of Baghdad, Baghdad, Iraq"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abir Jaafar","family":"Hussain","sequence":"additional","affiliation":[{"name":"Computer Science Department, Liverpool John Moores University, Byrom Street, Liverpool L33AF, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wasiq","family":"Khan","sequence":"additional","affiliation":[{"name":"Computer Science Department, Liverpool John Moores University, Byrom Street, Liverpool L33AF, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5166-4873","authenticated-orcid":false,"given":"Thar","family":"Baker","sequence":"additional","affiliation":[{"name":"Computer Science Department, Liverpool John Moores University, Byrom Street, Liverpool L33AF, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1688-0669","authenticated-orcid":false,"given":"Haya","family":"Al-Askar","sequence":"additional","affiliation":[{"name":"Computer Science Department, College of Engineering and Computer Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Janet","family":"Lunn","sequence":"additional","affiliation":[{"name":"Computer Science Department, Liverpool John Moores University, Byrom Street, Liverpool L33AF, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raghad","family":"Al-Shabandar","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Team, Datactics, Belfast BT1 3LG, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dhiya","family":"Al-Jumeily","sequence":"additional","affiliation":[{"name":"Computer Science Department, Liverpool John Moores University, Byrom Street, Liverpool L33AF, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5490-6030","authenticated-orcid":false,"given":"Panos","family":"Liatsis","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,20]]},"reference":[{"key":"ref_1","unstructured":"Nations, U. (2017). World Population Prospects: The 2017 Revision, Key Findings and Advance Tables, Departement of Economic and Social Affaire."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1080\/0964401042000310178","article-title":"Rethinking sustainable cities: Multilevel governance and the\u2019urban\u2019politics of climate change","volume":"14","author":"Bulkeley","year":"2005","journal-title":"Environ. Politics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/MM.2016.96","article-title":"Visual loT: Architectural Challenges and Opportunities","volume":"36","author":"Lyer","year":"2016","journal-title":"IEEE Micro"},{"key":"ref_4","first-page":"5","article-title":"Sensors, vision and networks: From video surveillance to activity recognition and health monitoring","volume":"11","author":"Andreaa","year":"2019","journal-title":"J. Ambient Intell. Smart Environ."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Hitendra Sarma, T., Sankar, V., and Shaik, R. (2020). Automatic Border Surveillance Using Machine Learning in Remote Video Surveillance Systems. Emerging Trends in Electrical, Communications, Information Technologies, Springer. Lecture Notes in Electrical Engineering.","DOI":"10.1007\/978-981-13-8942-9"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/978-3-030-11479-4_4","article-title":"Deep Learning for Driverless Vehicles","volume":"Volume 136","author":"Balas","year":"2019","journal-title":"Handbook of Deep Learning Applications. Smart Innovation, Systems and Technologies"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s11370-017-0224-y","article-title":"Multi-rotor drone tutorial: Systems, mechanics, control and state estimation","volume":"10","author":"Yang","year":"2017","journal-title":"Intell. Serv. Robot."},{"key":"ref_8","unstructured":"(2019, May 09). Australian Casino Uses Facial Recognition Cameras to Identify Potential Thieves\u2014FindBiometrics. FindBiometrics. Available online: https:\/\/findbiometrics.com\/australian-casino-facial-recognition-cameras-identify-potential-thieves\/."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MWC.2019.1800298","article-title":"Compressed Robust Transmission for Remote Sensing Services in Space Information Networks","volume":"26","author":"Lu","year":"2019","journal-title":"IEEE Wirel. Commun."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1109\/TCSVT.2014.2329353","article-title":"In-Block Prediction-Based Mixed Lossy and Lossless Reference Frame Recompression for Next-Generation Video Encoding","volume":"25","author":"Fan","year":"2015","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_11","unstructured":"Sharman, J. (2019, April 05). Metropolitan Police\u2019s facial recognition technology 98% inaccurate, figures show. Available online: https:\/\/www.independent.co.uk\/news\/uk\/home-news\/met-police-facial-recognition-success-south-wales-trial-home-office-false-positive-a8345036.html."},{"key":"ref_12","unstructured":"Burgess, M. (2019, March 11). Facial recognition tech used by UK police is making a ton of mistakes. Available online: https:\/\/www.wired.co.uk\/article\/face-recognition-police-uk-south-wales-met-notting-hill-carnival."},{"key":"ref_13","unstructured":"Blaschke, B. (2019, May 09). 90% of Macau ATMs now fitted with facial recognition technology\u2014IAG. IAG, 2018. [Online]. Available online: https:\/\/www.asgam.com\/index.php\/2018\/01\/02\/90-of-macau-atms-now-fitted-with-facial-recognition-technology\/."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/MM.2017.4241343","article-title":"Visual loT: Ultra-Low-Power Processing Architectures and Implications","volume":"37","author":"Chua","year":"2017","journal-title":"IEEE Micro"},{"key":"ref_15","unstructured":"Fox, C. (2019, May 09). Face Recognition Police Tools \u2018Staggeringly Inaccurate\u2019. Available online: https:\/\/www.bbc.co.uk\/news\/technology-44089161."},{"key":"ref_16","unstructured":"Ricardo, M., Marijn, J., and Devender, M. (2018). Data science empowering the public: Data-driven dashboards for transparent and accountable decision-making in smart cities. Gov. Inf. Q."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"543","DOI":"10.18287\/2412-6179-2016-40-4-543-551","article-title":"Onboard processing of hyperspectral data in the remote sensing systems based on hierarchical compression","volume":"40","author":"Gashnikov","year":"2016","journal-title":"Comput. Opt."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Liu, Z., Gao, L., Liu, Y., Guan, X., Ma, K., and Wang, Y. (2019). Efficient QoS Support for Robust Resource Allocation in Blockchain-based Femtocell Networks. IEEE Trans. Ind. Inform.","DOI":"10.1109\/TII.2019.2939146"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1109\/TMM.2016.2625276","article-title":"Utility-Driven Adaptive Preprocessing for Screen Content Video Compression","volume":"19","author":"Wang","year":"2017","journal-title":"IEEE Trans. Multimed."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/MMUL.2011.33","article-title":"Virtualized screen: A third element for cloud mobile convergence","volume":"18","author":"Lu","year":"2011","journal-title":"IEEE Multimed. Mag."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1109\/TMM.2012.2191945","article-title":"A Hybrid Algorithm for Effective Lossless Compression of Video Display Frames","volume":"14","author":"Kuo","year":"2012","journal-title":"IEEE Trans. Multimed."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1109\/TCSVT.2010.2045923","article-title":"A Lossless Embedded Compression Using Significant Bit Truncation for HD Video Coding","volume":"20","author":"Jaemoon","year":"2010","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1109\/TCOM.1985.1096398","article-title":"Predictive coding based on efficient motion estimation","volume":"33","author":"Srinivasan","year":"1985","journal-title":"IEEE Trans. Commun"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s11265-006-4190-4","article-title":"Survey on Block Matching Motion Estimation Algorithms and Architectures with New Results","volume":"42","author":"Huang","year":"2006","journal-title":"J. Vlsi Signal Process."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/0004-3702(81)90024-2","article-title":"Determining Optical Flow","volume":"17","author":"Horn","year":"1981","journal-title":"Artifical Intell."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Richardson, I.E.G. (2010). The H.264 Advanced Video Compression Standard, John Wiley & Sons Inc. [2nd ed.].","DOI":"10.1002\/9780470989418"},{"key":"ref_27","unstructured":"ISO\/IEC (2020, February 01). Information Technology\u2013Coding of Moving Pictures and Associated Audio for Digital Storage Media at up to about 1,5 Mbit\/s\u2013Part 2: Video. Available online: https:\/\/www.iso.org\/standard\/22411.html."},{"key":"ref_28","unstructured":"ISO\/IEC (2020, February 01). Information Technology\u2013Generic Coding of Moving Pictures and Associated Audio\u2013Part 2: Video, Available online: https:\/\/www.iso.org\/standard\/61152.html."},{"key":"ref_29","unstructured":"ITU-T and ISO\/IEC (2020, February 01). Advanced Video Coding for Generic Audiovisual Services; H.264, MPEG, 14496\u201310, Available online: https:\/\/www.itu.int\/ITU-T\/recommendations\/rec.aspx?rec=11466."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Sullivan, G., Topiwala, P., and Luthra, A. (2004, January 2\u20136). The H.264\/AVC Advanced Video Coding Standard: Overview and Introduction to the Fidelity Range Extensions. Proceedings of the SPIE conference on Applications of Digital Image Processing XXVII, Denver, CO, USA.","DOI":"10.1117\/12.564457"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/JPROC.2004.839617","article-title":"Video Compression\u2014From Concepts to the H.264\/AVC Standard","volume":"93","author":"Sullivan","year":"2005","journal-title":"Proc. IEEE"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1109\/MSP.2012.2219672","article-title":"High Efficiency Video Coding: The Next Frontier in Video Compression [Standards in a Nutshell]","volume":"30","author":"Ohm","year":"2013","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.1007\/978-3-319-32467-8_88","article-title":"Video Compression Using Variable Block Size Motion Compensation with Selective Subpixel Accuracy in Redundant Wavelet Transform","volume":"448","author":"Suliman","year":"2016","journal-title":"Adv. Intell. Syst. Comput."},{"key":"ref_34","unstructured":"Kim, C. (2010). Complexity Adaptation in Video Encoders for Power Limited Platforms, Dublin City University."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3708","DOI":"10.1007\/s40314-017-0539-5","article-title":"Compact video content representation for video coding using low multi-linear tensor rank approximation with dynamic core tensor order","volume":"37","author":"Suganya","year":"2018","journal-title":"Comput. Appl. Math."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Chen, D., Tang, Y., Zhang, H., Wang, L., and Li, X. (2020). Incremental Factorization of Big Time Series Data with Blind Factor Approximation. IEEE Trans. Knowl. Data Eng.","DOI":"10.1109\/TKDE.2019.2931687"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1631\/jzus.C0910684","article-title":"Review of the current and future technologies for video compression","volume":"11","author":"Yu","year":"2010","journal-title":"J. Zhejiang Univ. Sci. C"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1930","DOI":"10.1109\/TVLSI.2018.2842179","article-title":"A Single-Chip 4K 60-fps 4:2:2 HEVC Video Encoder LSI Employing Efficient Motion Estimation and Mode Decision Framework with Scalability to 8K","volume":"26","author":"Onishi","year":"2018","journal-title":"IEEE Trans. Large Scale Integr. (VLSI) Syst."},{"key":"ref_39","unstructured":"Barjatya, A. (2004). Block Matching Algorithms for Motion Estimation, DIP 6620 Spring."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"282","DOI":"10.3844\/jcssp.2008.282.289","article-title":"Simplified Block Matching Algorithm for Fast Motion Estimation in Video Compression","volume":"4","author":"Ezhilarasan","year":"2008","journal-title":"J. Comput. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Sayood, K. (2006). Introduction to Data Compression, Morgan Kaufmann. [3rd ed.].","DOI":"10.1016\/B978-012620862-7\/50018-3"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.neucom.2018.10.060","article-title":"A survey on video compression fast block matching algorithms","volume":"335","author":"Hussain","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1557","DOI":"10.1049\/iet-ipr.2017.0641","article-title":"Efficient direction-oriented search algorithm for block motion estimation","volume":"12","author":"Shinde","year":"2018","journal-title":"IET Image Process."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.compeleceng.2011.01.003","article-title":"Architecture design of variable block size motion estimation for full and fast search algorithms in H.264\/AVC","volume":"37","author":"Xiong","year":"2011","journal-title":"Comput. Electr. Eng."},{"key":"ref_45","unstructured":"Al-Mualla, M.E., Canagarajah, C.N., and Bull, D.R. (2002). Video Coding for Mobile Communications: Efficiency, Complexity and Resilience, Academic Press."},{"key":"ref_46","unstructured":"Koga, T., Ilinuma, K., Hirano, A., Iijima, Y., and Ishiguro, Y. (1981). Motion Compensated Interframe Coding for Video Conferencin, the Proc National Telecommum."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1109\/76.313138","article-title":"A new three-step search algorithm for block motion estimation","volume":"4","author":"Reoxiang","year":"1994","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1109\/76.499840","article-title":"A novel four-step search algorithm for fast block motion estimation","volume":"6","year":"1996","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_49","unstructured":"Shan, Z., and Kai-Kuang, M. (1997, January 12). A new diamond search algorithm for fast block matching motion estimation. Proceedings of the ICICS, 1997 International Conference on Information, Communications and Signal Processing, Singapore."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1109\/76.564122","article-title":"A simple and efficient search algorithm for block-matching motion estimation","volume":"7","author":"Jianhua","year":"1997","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1442","DOI":"10.1109\/TIP.2002.806251","article-title":"Adaptive rood pattern search for fast block-matching motion estimation","volume":"11","author":"Nie","year":"2002","journal-title":"IEEE Trans Image Process."},{"key":"ref_52","unstructured":"Yi, X., Zhang, J., Ling, N., and Shang, W. (, January July). Improved and simplified fast motion estimation for JM (JVT-P021). Proceedings of the Joint Video Team (JVT) of ISO\/IEC MPEG & ITU-T VCEG (ISO\/IEC JTC1\/SC29\/WG11 and ITU-T SG16 Q.6) 16th Meeting, Poznan, Poland."},{"key":"ref_53","first-page":"225","article-title":"joint adaptive block matching search algorithm","volume":"56","author":"Ananthashayana","year":"2009","journal-title":"World Acad. Sci. Eng. Technol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1109\/76.875508","article-title":"A fast full-search motion-estimation algorithm using representative pixels and adaptive matching scan","volume":"10","year":"2000","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_55","first-page":"1493","article-title":"An adaptive fast full search motion estimation algorithm for H.264","volume":"2","year":"2005","journal-title":"Ieee Int. Symp. Circuits Syst. ISCAS"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2355","DOI":"10.1109\/TSP.2002.801888","article-title":"Fast full search motion estimation algorithm using early detection of impossible candidate vectors","volume":"50","year":"2002","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1109\/5326.983938","article-title":"Fast Full Search Motion Estimation Algorithm Using various Matching Scans in Video Coding","volume":"31","year":"2001","journal-title":"IEEE Trans. Syst. Mancybern. Part C Appl. Rev."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Xiao, J., Zhu, R., Hu, R., Wang, M., Zhu, Y., Chen, D., and Li, D. (2018). Towards Real-Time Service from Remote Sensing: Compression of Earth Observatory Video Data via Long-Term Background Referencing. Remote Sens., 10.","DOI":"10.3390\/rs10060876"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Allauddin, M.S., Kiran, G.S., Kiran, G.R., Srinivas, G., Mouli GU, R., and Prasad, P.V. (August, January 28). Development of a Surveillance System for Forest Fire Detection and Monitoring using Drones. Proceedings of the IGARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8900436"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"15804","DOI":"10.1109\/ACCESS.2019.2892716","article-title":"Analysis and Optimization of Unmanned Aerial Vehicle Swarms in Logistics: An Intelligent Delivery Platform","volume":"7","author":"Kuru","year":"2019","journal-title":"IEEE Access"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/6\/1004\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:10:15Z","timestamp":1760173815000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/6\/1004"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,20]]},"references-count":60,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["rs12061004"],"URL":"https:\/\/doi.org\/10.3390\/rs12061004","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,20]]}}}