Zobrazeno 1 - 10
of 274
pro vyhledávání: '"Benoit Vozel"'
Publikováno v:
Remote Sensing, Vol 16, Iss 12, p 2093 (2024)
Lossy compression of remote-sensing images is a typical stage in their processing chain. In design or selection of methods for lossy compression, it is commonly assumed that images are noise-free. Meanwhile, there are many practical situations where
Externí odkaz:
https://doaj.org/article/ad334a5868b040ca8eded651736c18ba
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 8, Iss 4, Pp 1164-1165 (2023)
Externí odkaz:
https://doaj.org/article/0ece93d1ce744caa8f1dd00613b51b86
Publikováno v:
Remote Sensing, Vol 15, Iss 6, p 1669 (2023)
Nowadays, there is a clear trend toward increasing the number of remote-sensing images acquired and their average size. This leads to the need to compress the images for storage, dissemination, and transfer over communication lines where lossy compre
Externí odkaz:
https://doaj.org/article/59de2c20a6b748b0a8a9cfc28db19bb2
Publikováno v:
Applied Sciences, Vol 12, Iss 15, p 7555 (2022)
With a resolution improvement, the size of modern remote sensing images increases. This makes it desirable to compress them, mostly by using lossy compression techniques. Often the images to be compressed (or some component images of multichannel rem
Externí odkaz:
https://doaj.org/article/5c3bacda85de4dc1a78afe851c732626
Publikováno v:
Sensors, Vol 22, Iss 3, p 1231 (2022)
Finding putative correspondences between a pair of images is an important prerequisite for image registration. In complex cases such as multimodal registration, a true match could be less plausible than a false match within a search zone. Under these
Externí odkaz:
https://doaj.org/article/61e26e2dae634737bcb75ca2821c0413
Autor:
Victor Makarichev, Irina Vasilyeva, Vladimir Lukin, Benoit Vozel, Andrii Shelestov, Nataliia Kussul
Publikováno v:
Remote Sensing, Vol 14, Iss 1, p 125 (2021)
Lossy compression of remote sensing data has found numerous applications. Several requirements are usually imposed on methods and algorithms to be used. A large compression ratio has to be provided, introduced distortions should not lead to sufficien
Externí odkaz:
https://doaj.org/article/94afb311d0d744b795f48551445aa039
Publikováno v:
Remote Sensing, Vol 13, Iss 18, p 3727 (2021)
A huge amount of remote sensing data is acquired each day, which is transferred to image processing centers and/or to customers. Due to different limitations, compression has to be applied on-board and/or on-the-ground. This Special Issue collects 15
Externí odkaz:
https://doaj.org/article/432f4a6c5fa44fd49826fe46180860ca
Autor:
Vladimir Lukin, Irina Vasilyeva, Sergey Krivenko, Fangfang Li, Sergey Abramov, Oleksii Rubel, Benoit Vozel, Kacem Chehdi, Karen Egiazarian
Publikováno v:
Remote Sensing, Vol 12, Iss 22, p 3840 (2020)
Lossy compression is widely used to decrease the size of multichannel remote sensing data. Alongside this positive effect, lossy compression may lead to a negative outcome as making worse image classification. Thus, if possible, lossy compression sho
Externí odkaz:
https://doaj.org/article/2255d1b0cc3048689711bef18c2cf8bf
Publikováno v:
Remote Sensing, Vol 12, Iss 4, p 703 (2020)
Detecting similarities between image patches and measuring their mutual displacement are important parts in the registration of multimodal remote sensing (RS) images. Deep learning approaches advance the discriminative power of learned similarity mea
Externí odkaz:
https://doaj.org/article/17ecf966fba048118d65158ea22a0efa
Publikováno v:
Current Overview on Science and Technology Research Vol. 9 ISBN: 9789355479716
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07daaa4da2410cbca5a4ee949fcd5156
https://doi.org/10.9734/bpi/costr/v9/4316a
https://doi.org/10.9734/bpi/costr/v9/4316a
