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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 5/2017

30-04-2016 | Original Article

The mean shift method of chaotic sequences in the study of compressive sensing

Published in: International Journal of Machine Learning and Cybernetics | Issue 5/2017

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Abstract

This paper presents a novel reconstruction approach of digital image in compressive sensing by the use of mean shift of different chaotic sequence to the measurement matrix. This matrix preserves better details of the structures of the recovered images, and enables a systematic construction of the measurement matrices of it. This proposed approach provides not only visible Peak Signal to Noise Ratio improvements over state-of-the-art methods (e.g. the Gaussian random matrix method) but also better preservation of the image structures during compression, which in turn enables better visual quality in image recovery, as illustrated in our experimental results.
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Metadata
Title
The mean shift method of chaotic sequences in the study of compressive sensing
Publication date
30-04-2016
Published in
International Journal of Machine Learning and Cybernetics / Issue 5/2017
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0534-y

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