Compression of Multitemporal Remote Sensing Images Through Bayesian Segmentation

Multi-temporal remote sensing images are useful tools for many applications in natural resource management. Compression of this kind of data is an issue of interest, yet, only a few paper address it specifically, while general-purpose compression algorithms are not well suited to the problem, as they do not exploit the strong correlation among images of a multi-temporal set of data. Here, the authors propose a coding architecture for multi-temporal images, which takes advantage of segmentation in order to compress data. Segmentation subdivides images into homogeneous regions, which can be efficiently and independently encoded. Moreover this architecture provides the user with a great flexibility in transmitting and retrieving only data of interest.

Provided by: Telecom of New Zealand Topic: Networking Date Added: Jan 2013 Format: PDF

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