ISBN-13: 9783639096910 / Angielski / Miękka / 2008 / 160 str.
Hyperspectral imaging is a powerful technique and has been used in a large number of applications. However, it generates massively large image data sets. Access and transport of these data sets will stress existing processing, storage and transmission capabilities. A new embedded, block-based, wavelet transform coding algorithm of low complexity is developed for hyperspectral image compression: Three-Dimensional Set Partitioned Embedded bloCK (3D-SPECK). 3D-SPECK efficiently encodes 3D volumetric hyperspectral image data by exploiting the dependencies in all dimensions. It can generate either SNR scalable or resolution scalable embedded bitstreams. It can also generate ROI retrievable bitstreams. This book introduces 3D-SPECK and describes its technical details. It is demonstrated that 3D-SPECK has excellent performance on hyperspectral image compression.
Hyperspectral imaging is a powerful technique and has been used in a large number of applications. However, it generates massively large image data sets. Access and transport of these data sets will stress existing processing, storage and transmission capabilities. A new embedded, block-based, wavelet transform coding algorithm of low complexity is developed for hyperspectral image compression: Three-Dimensional Set Partitioned Embedded bloCK (3D-SPECK). 3D-SPECK efficiently encodes 3D volumetric hyperspectral image data by exploiting the dependencies in all dimensions. It can generate either SNR scalable or resolution scalable embedded bitstreams. It can also generate ROI retrievable bitstreams.This book introduces 3D-SPECK and describes its technical details. It is demonstrated that 3D-SPECK has excellent performance on hyperspectral image compression.