TY - JOUR
T1 - JPEG2000 encoding of remote sensing multispectral images with no-data regions
AU - González-Conejero, Jorge
AU - Bartrina-Rapesta, Joan
AU - Serra-Sagristà, Joan
PY - 2010/4/1
Y1 - 2010/4/1
N2 - Most sensors used for remote sensing (RS) purposes capture more than one component to seize different features from the Earth's surface. Usually, either multispectral images acquired for RS applications are corrected or the user/application determines valid regions within the image. Consequently, regions without information may emerge (no-data regions). This letter proposes to encode multispectral images with no-data regions through the JPEG2000 framework, taking into account the lack of importance of these irrelevant regions. Experimental results, performed on data from real scenarios, suggest that the best approach analyzed is the shape-adaptive (SA) Karhunen-Loêve transform to decorrelate the spectral redundancy and then the SA multicomponent JPEG2000. The coding-performance improvement over other coding systems considered (Binary Set Splitting with K-D Trees, SAWavelet Difference Reduction, and SA TARP) is from 5 to 20 dB in signal-to-noise ratio energy. © 2006 IEEE.
AB - Most sensors used for remote sensing (RS) purposes capture more than one component to seize different features from the Earth's surface. Usually, either multispectral images acquired for RS applications are corrected or the user/application determines valid regions within the image. Consequently, regions without information may emerge (no-data regions). This letter proposes to encode multispectral images with no-data regions through the JPEG2000 framework, taking into account the lack of importance of these irrelevant regions. Experimental results, performed on data from real scenarios, suggest that the best approach analyzed is the shape-adaptive (SA) Karhunen-Loêve transform to decorrelate the spectral redundancy and then the SA multicomponent JPEG2000. The coding-performance improvement over other coding systems considered (Binary Set Splitting with K-D Trees, SAWavelet Difference Reduction, and SA TARP) is from 5 to 20 dB in signal-to-noise ratio energy. © 2006 IEEE.
KW - Decorrelation transform
KW - JPEG2000
KW - Karhunen-Loêve transform (KLT)
KW - No-data region coding
KW - Remote sensing (RS)
KW - Shape-adaptive (SA)
U2 - 10.1109/LGRS.2009.2032370
DO - 10.1109/LGRS.2009.2032370
M3 - Article
SN - 1545-598X
VL - 7
SP - 251
EP - 255
JO - IEEE Geoscience and Remote Sensing Letters
JF - IEEE Geoscience and Remote Sensing Letters
M1 - 5308311
ER -