Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems
There is a need for improvement of tools to deal with large volumes of multimedia data effectively. In particular, real-time data processing is one of the major problems for multimedia data computing in remote sensing systems. Such big data systems have to offer effective management and computationa...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
| Online Access: | https://ieeexplore.ieee.org/document/9171825/ |
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| author | Rahul Malik Aditya Khamparia Sahil Garg Deepak Gupta Bong Jun Choi M. Shamim Hossain |
| author_facet | Rahul Malik Aditya Khamparia Sahil Garg Deepak Gupta Bong Jun Choi M. Shamim Hossain |
| author_sort | Rahul Malik |
| collection | DOAJ |
| description | There is a need for improvement of tools to deal with large volumes of multimedia data effectively. In particular, real-time data processing is one of the major problems for multimedia data computing in remote sensing systems. Such big data systems have to offer effective management and computational efficiency for applications in real-time. In this paper, we propose a large-scale geological processing method for aerial Light Detection and Ranging (LiDAR) clouds containing multimedia data that ensures mobility and timeliness. By utilizing Spark and Cassandra, our proposed approach can significantly reduce the execution time of the time-consuming process. We investigate fast ground-only raster generation from huge LiDAR datasets. We observed that filtered cloud data ensuing from impartial consideration of neighboring zones could lead to classification errors on the boundaries. Therefore, an integrated approach is proposed to correct these errors to improve the classification consistency, achieve faster processing time, provide automatic error correction, obtain Digital Terrain Models (DTM), and minimize user intervention. These features can provide a framework for an on-demand DTM output and scalable application services. Furthermore, the proposed approach can expect to benefit other real-time applications in LiDAR systems. |
| format | Article |
| id | doaj-art-7b2deeb5ae2a458f95161d7e7ce751ec |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-7b2deeb5ae2a458f95161d7e7ce751ec2025-08-20T02:31:05ZengIEEEIEEE Access2169-35362020-01-01815354615356010.1109/ACCESS.2020.30183269171825Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing SystemsRahul Malik0Aditya Khamparia1https://orcid.org/0000-0001-9019-8230Sahil Garg2https://orcid.org/0000-0003-0229-608XDeepak Gupta3https://orcid.org/0000-0002-3019-7161Bong Jun Choi4https://orcid.org/0000-0002-6550-749XM. Shamim Hossain5https://orcid.org/0000-0001-5906-9422School of Computer Science and Engineering, Lovely Professional University, Phagwara, IndiaSchool of Computer Science and Engineering, Lovely Professional University, Phagwara, IndiaElectrical Engineering Department, École de technologie supérieure, Montréal, QC, CanadaDepartment of Computer Science Engineering, Maharaja Agrasen Institute of Technology, New Delhi, IndiaSchool of Computer Science and Engineering, Soongsil University, Seoul, South KoreaDepartment of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi ArabiaThere is a need for improvement of tools to deal with large volumes of multimedia data effectively. In particular, real-time data processing is one of the major problems for multimedia data computing in remote sensing systems. Such big data systems have to offer effective management and computational efficiency for applications in real-time. In this paper, we propose a large-scale geological processing method for aerial Light Detection and Ranging (LiDAR) clouds containing multimedia data that ensures mobility and timeliness. By utilizing Spark and Cassandra, our proposed approach can significantly reduce the execution time of the time-consuming process. We investigate fast ground-only raster generation from huge LiDAR datasets. We observed that filtered cloud data ensuing from impartial consideration of neighboring zones could lead to classification errors on the boundaries. Therefore, an integrated approach is proposed to correct these errors to improve the classification consistency, achieve faster processing time, provide automatic error correction, obtain Digital Terrain Models (DTM), and minimize user intervention. These features can provide a framework for an on-demand DTM output and scalable application services. Furthermore, the proposed approach can expect to benefit other real-time applications in LiDAR systems.https://ieeexplore.ieee.org/document/9171825/ |
| spellingShingle | Rahul Malik Aditya Khamparia Sahil Garg Deepak Gupta Bong Jun Choi M. Shamim Hossain Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems IEEE Access |
| title | Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems |
| title_full | Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems |
| title_fullStr | Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems |
| title_full_unstemmed | Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems |
| title_short | Notice of Violation of IEEE Publication Principles: Reversible Data Hiding and Smart Multimedia Computing Using Big Data in Remote Sensing Systems |
| title_sort | notice of violation of ieee publication principles reversible data hiding and smart multimedia computing using big data in remote sensing systems |
| url | https://ieeexplore.ieee.org/document/9171825/ |
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