TY - JOUR
T1 - Rate allocation method for the FAst transmission of pre-encoded meteorological data over JPIP
AU - Jiménez-Rodríguez, Leandro
AU - Aulí-Llinàs, Francesc
AU - Muñoz-Gómez, Juan
AU - Bartrina-Rapesta, Joan
AU - Blanes, Ian
AU - Serra-Sagristà, Joan
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - This work addresses the transmission of pre-encoded video containing meteorological data over JPIP. The primary requirement for the rate allocation algorithm deployed in the JPIP server is the real-time processing demands of the application. A secondary requirement for the proposed algorithm is that it should be able to either minimize the mean squared error (MMSE) of the video sequence, or minimize the maximum distortion (MMAX). The MMSE criterion considers the minimization of the overall distortion, whereas MMAX achieves pseudo-constant quality for all frames. The proposed rate allocation method employs the FAst rate allocation through STeepest descent (FAST) method that was initially developed for video-on-demand applications. The adaptation of FAST in the proposed remote sensing scenario considers meteorological data captured by the European meteorological satellites (Meteosat). Experimental results suggest that FAST can be successfully adopted in remote sensing scenarios.
AB - This work addresses the transmission of pre-encoded video containing meteorological data over JPIP. The primary requirement for the rate allocation algorithm deployed in the JPIP server is the real-time processing demands of the application. A secondary requirement for the proposed algorithm is that it should be able to either minimize the mean squared error (MMSE) of the video sequence, or minimize the maximum distortion (MMAX). The MMSE criterion considers the minimization of the overall distortion, whereas MMAX achieves pseudo-constant quality for all frames. The proposed rate allocation method employs the FAst rate allocation through STeepest descent (FAST) method that was initially developed for video-on-demand applications. The adaptation of FAST in the proposed remote sensing scenario considers meteorological data captured by the European meteorological satellites (Meteosat). Experimental results suggest that FAST can be successfully adopted in remote sensing scenarios.
KW - Interactive image transmission
KW - Rate allocation
KW - Rate-distortion optimization
UR - https://www.scopus.com/pages/publications/77957836887
U2 - 10.1117/12.860619
DO - 10.1117/12.860619
M3 - Artículo
AN - SCOPUS:77957836887
SN - 0277-786X
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
ER -