Abstract
In this paper we present a new prediction technique to compress a pair of satellite images that have significant overlap in the underlying spatial areas. When this prediction technique is combined with an existing lossless image set compression algorithm, the results are significantly better than those obtained by compressing each image individually. Even when there are significant differences between the two images due to factors such as seasonal and atmospheric variations, the new prediction technique still performs very well to achieve significant reduction in storage requirements.
This research was supported by a MITACS Accelerate Internship with Iunctus Geomatics Corp. (VT) and an NSERC Discovery Grant (HC).
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Trivedi, V., Cheng, H. (2011). Lossless Compression of Satellite Image Sets Using Spatial Area Overlap Compensation. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21596-4_25
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DOI: https://doi.org/10.1007/978-3-642-21596-4_25
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