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dc.contributor.author
D'amato, Juan Pablo  
dc.date.available
2024-01-26T13:30:40Z  
dc.date.issued
2023-04  
dc.identifier.citation
D'amato, Juan Pablo; FitDepth: fast and lite 16-bit depth image compression algorithm; Springer; Journal on Image and Video Processing; 2023; 1; 4-2023; 1-17  
dc.identifier.issn
1687-5281  
dc.identifier.uri
http://hdl.handle.net/11336/224970  
dc.description.abstract
This article presents a fast parallel lossless technique and a lossy image compression technique for 16-bit single-channel images. Nowadays, such techniques are “a must” in robotics and other areas where several depth cameras are used. Since many of these algorithms need to be run in low-profile hardware, as embedded systems, they should be very fast and customizable. The proposal is based on the consideration of depth images as surfaces, so the idea is to split the image into a set of polynomial functions that each describes a part of the surface. The developed algorithm herein proposed can achieve a similar—or better—compression rate and especially higher speed rates than the existing techniques. It also has the potential of being fully parallelizable and to run on several cores. This feature, compared to other approaches, makes it useful for handling and streaming multiple cameras simultaneously. The algorithm is assessed in different situations and hardware. Its implementation is rather simple and is carried out with LIDAR captured images. Therefore, this work is accompanied by an open implementation in C++.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
DEPTH IMAGE  
dc.subject
FAST COMPRESSION  
dc.subject
PARALLEL IMPLEMENTATION  
dc.subject.classification
Ciencias de la Computación  
dc.subject.classification
Ciencias de la Computación e Información  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
FitDepth: fast and lite 16-bit depth image compression algorithm  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2024-01-25T14:10:03Z  
dc.journal.volume
2023  
dc.journal.number
1  
dc.journal.pagination
1-17  
dc.journal.pais
Suecia  
dc.description.fil
Fil: D'amato, Juan Pablo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina  
dc.journal.title
Journal on Image and Video Processing  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://jivp-eurasipjournals.springeropen.com/articles/10.1186/s13640-023-00606-z  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1186/s13640-023-00606-z