Zobrazeno 1 - 10
of 166
pro vyhledávání: '"Joan Serra-Sagrista"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12169-12180 (2024)
Fixed-quality image compression is a coding paradigm where the tolerated introduced distortion is set by the user. This article proposes a novel fixed-quality compression method for remote sensing images. It is based on a neural architecture we have
Externí odkaz:
https://doaj.org/article/93c987e6c898476b84ad05f49d475b36
Autor:
Miguel Hernandez-Cabronero, David Evans, Joan Bartrina-Rapesta, Francesc Auli-Llinas, Ian Blanes, Joan Serra-Sagrista
Publikováno v:
IEEE Access, Vol 12, Pp 36702-36711 (2024)
The Consultative Committee for Space Data Systems (CCSDS) recently published a lossless compression standard for housekeeping and telemetry. These data are critical for the safe and productive operation of virtually all remote sensing missions, inclu
Externí odkaz:
https://doaj.org/article/fb7bc4e62d0847ff8c7b7302423351f1
Autor:
Pau Galles, Katalin Takats, Miguel Hernandez-Cabronero, David Berga, Luciano Pega, Laura Riordan-Chen, Clara Garcia, Guillermo Becker, Adan Garriga, Anica Bukva, Joan Serra-Sagrista, David Vilaseca, Javier Marin
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3285-3296 (2024)
iquaflow is a framework that provides a set of tools to assess image quality. The user can add custom metrics that can be easily integrated and a set of unsupervised methods is offered by default. Furthermore, iquaflow measures quality by using the p
Externí odkaz:
https://doaj.org/article/18c255c09b0a477aae1dc4e4b8afad95
Autor:
Bachir Kaddar, Hadria Fizazi, Miguel Hernandez-Cabronero, Victor Sanchez, Joan Serra-Sagrista
Publikováno v:
IEEE Access, Vol 9, Pp 105892-105901 (2021)
Designing small and efficient mobile neural networks is difficult because the challenge is to determine the architecture that achieves the best performance under a given limited computational scenario. Previous lightweight neural networks rely on a c
Externí odkaz:
https://doaj.org/article/645aad8c01c44835b6f8001641a87f91
Publikováno v:
IEEE Access, Vol 8, Pp 81283-81297 (2020)
Efficient high-throughput (HT) compression algorithms are paramount to meet the stringent constraints of present and upcoming data storage, processing, and transmission systems. In particular, latency, bandwidth and energy requirements are critical f
Externí odkaz:
https://doaj.org/article/9c96f9385cee4c64be5c82a39005a07d
Publikováno v:
IEEE Access, Vol 7, Pp 103918-103930 (2019)
Predictive image coding systems yield a high-compression performance at low computational complexity, and are therefore popular in standards and prominent coding techniques for both lossless and near-lossless compression. However, few prediction-base
Externí odkaz:
https://doaj.org/article/8fb2a03cfd994bae92148e972c1b77c8
Publikováno v:
IEEE Access, Vol 7, Pp 115857-115870 (2019)
In this paper, we provide a method to obtain tight lower bounds on the minimum redundancy achievable by a Huffman code when the probability distribution underlying an alphabet is only partially known. In particular, we address the case where the occu
Externí odkaz:
https://doaj.org/article/2cc1cabdf8a54b38a0ff4de7a11d662b
Autor:
Antonio Sanchez, Ian Blanes, Yubal Barrios, Miguel Hernandez-Cabronero, Joan Bartrina-Rapesta, Joan Serra-Sagrista, Roberto Sarmiento
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Altres ajuts: European Space Agency (ESA) (Grant Number: 4000136723/22/NL/CRS) On-board multi- and hyperspectral instruments acquire large volumes of data that need to be processed with the limited computational and storage resources. In this context
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8807759b405404bdf642dd7c54a2f9f0
https://doi.org/10.1109/lgrs.2022.3213975
https://doi.org/10.1109/lgrs.2022.3213975
Autor:
Ian Blanes, Joan Serra-Sagrista, Kevin Chow, Miguel Hernandez-Cabronero, Dion Eustathios Olivier Tzarmarias
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::917f63b132f5b0a21426ddb2b3b7ac22
https://doi.org/10.1109/lgrs.2021.3084065
https://doi.org/10.1109/lgrs.2021.3084065
Publikováno v:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 31
The increase in popularity of point-cloud-oriented applications has triggered the development of specialized compression algorithms. In this paper, a novel algorithm is developed for the lossless geometry compression of voxelized point clouds followi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f262074084baf0c03bee2df9e56d354c
https://pubmed.ncbi.nlm.nih.gov/35763478
https://pubmed.ncbi.nlm.nih.gov/35763478