FitDepth: fast and lite 16-bit depth image compression algorithm
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-pr...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-04-01
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| Series: | EURASIP Journal on Image and Video Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13640-023-00606-z |
| _version_ | 1797849891963142144 |
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| author | Juan P. D’Amato |
| author_facet | Juan P. D’Amato |
| author_sort | Juan P. D’Amato |
| collection | DOAJ |
| 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++. |
| first_indexed | 2024-04-09T18:51:27Z |
| format | Article |
| id | doaj.art-3bafd0537b7d4f289c27b57e905cfc2f |
| institution | Directory Open Access Journal |
| issn | 1687-5281 |
| language | English |
| last_indexed | 2024-04-09T18:51:27Z |
| publishDate | 2023-04-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Image and Video Processing |
| spelling | doaj.art-3bafd0537b7d4f289c27b57e905cfc2f2023-04-09T11:24:24ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812023-04-012023111710.1186/s13640-023-00606-zFitDepth: fast and lite 16-bit depth image compression algorithmJuan P. D’Amato0Pladema Institute, Campus Universitario, UNICENAbstract 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++.https://doi.org/10.1186/s13640-023-00606-zDepth imageFast compressionParallel implementation |
| spellingShingle | Juan P. D’Amato FitDepth: fast and lite 16-bit depth image compression algorithm EURASIP Journal on Image and Video Processing Depth image Fast compression Parallel implementation |
| title | FitDepth: fast and lite 16-bit depth image compression algorithm |
| title_full | FitDepth: fast and lite 16-bit depth image compression algorithm |
| title_fullStr | FitDepth: fast and lite 16-bit depth image compression algorithm |
| title_full_unstemmed | FitDepth: fast and lite 16-bit depth image compression algorithm |
| title_short | FitDepth: fast and lite 16-bit depth image compression algorithm |
| title_sort | fitdepth fast and lite 16 bit depth image compression algorithm |
| topic | Depth image Fast compression Parallel implementation |
| url | https://doi.org/10.1186/s13640-023-00606-z |
| work_keys_str_mv | AT juanpdamato fitdepthfastandlite16bitdepthimagecompressionalgorithm |