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Lossless Satellite Data Compression
2013Satellite sensors produce enormous data volumes, especially hyperspectral sensors that acquire over hundreds of images of narrow-wavelength bands and produce an image cube. Thus, a lot of effort has been made to study moreefficient ways to compress satellite images or image cubes. Compression techniques can be classified into three types: 1.
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Lossless Data Compression at Pragmatic Rates
2025 IEEE International Symposium on Information Theory (ISIT)Andreas Theocharous +1 more
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Efficient Lossless Data Compression"
This work presents a novel lossless compression algorithm designed for efficient and high-performance data reduction. The research is written in both English and Arabic."openaire +1 more source
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
IEEE Transactions on Image Processing, 2000M J Weinberger +2 more
exaly
Information Hiding on Lossless Data Compression
2006 International Conference on Intelligent Information Hiding and Multimedia, 2006Katsunari Yoshioka +3 more
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Optimized Onboard Lossless and Near-Lossless Compression of Hyperspectral Data Using CALIC
IEEE Geoscience and Remote Sensing Letters, 2004Enrico Magli, G Olmo
exaly
An Encryption-then-Compression System for Lossless Image Compression Standards
IEICE Transactions on Information and Systems, 2017Shoko Imaizumi +2 more
exaly
Lossless and near lossless compression of real color filter array data
IEEE Transactions on Consumer Electronics, 2008Karen Egiazarian
exaly