Results 11 to 20 of about 78,363 (276)
Quasi-linear Compressed Sensing [PDF]
Multiscale Modeling & Simulation, 2014 Inspired by significant real-life applications, in particular, sparse phase retrieval and sparse pulsation frequency detection in Asteroseismology, we investigate a general framework for compressed sensing, where the measurements are quasi-linear.
Martin Ehler +2 more
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Compression-Based Compressed Sensing [PDF]
IEEE Transactions on Information Theory, 2017 Modern compression algorithms exploit complex structures that are present in signals to describe them very efficiently. On the other hand, the field of compressed sensing is built upon the observation that "structured" signals can be recovered from their under-determined set of linear projections.
Farideh E. Rezagah +3 more
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Hierarchical Compressed Sensing
, 2022 Compressed sensing is a paradigm within signal processing that provides the means for recovering structured signals from linear measurements in a highly efficient manner. Originally devised for the recovery of sparse signals, it has become clear that a similar methodology would also carry over to a wealth of other classes of structured signals. In this
Eisert, Jens +4 more
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An Overview on Deep Learning Techniques for Video Compressive Sensing
Applied Sciences, 2022 The use of compressive sensing in several applications has allowed to capture impressive results, especially in various applications such as image and video processing and it has become a promising direction of scientific research.
Wael Saideni +3 more
doaj +1 more source
A secure image permutation–substitution framework based on chaos and compressive sensing
International Journal of Distributed Sensor Networks, 2020 Existing secure image acquisition works based on compressive sensing, viewing compressive sensing–based imaging system as a symmetric cryptosystem, can only achieve asymptotic spherical security denoting that the ciphertext only leaks information about ...
Rui Zhang, Di Xiao
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Video Compressive Sensing Reconstruction Algorithm Based on 3D Tree Structure and Bayesian Model [PDF]
Jisuanji gongcheng, 2016 In view of the traditional underwater video coding requiring higher underwater acoustic channel and the scenes of underwater video with uneven illumination being complex and not fixed,this paper presents a reconstruction algorithm with Three Dimension(3D)
ZHUANG Yanbin,WANG Zunzhi,XIAO Xianjian,ZHANG Xuewu
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Compressive Sensing over OFDM Systems
Journal of Kufa for Mathematics and Computer, 2021 Communications development is the fastest-growing Nowadays, so the need and the constant demand for faster and more reliable communication methods have increased. Here, the compressive sensing appeared to meet this need.
Zainab Al-Shably, Zahir Hussain
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Measure What Should be Measured: Progress and Challenges in Compressive Sensing [PDF]
, 2012 Is compressive sensing overrated? Or can it live up to our expectations? What will come after compressive sensing and sparsity? And what has Galileo Galilei got to do with it? Compressive sensing has taken the signal processing community by storm.
Strohmer, Thomas
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Application of Compressive Sensing in the Presence of Noise for Transient Photometric Events
Signals, 2022 Compressive sensing is a simultaneous data acquisition and compression technique, which can significantly reduce data bandwidth, data storage volume, and power. We apply this technique for transient photometric events. In this work, we analyze the effect
Asmita Korde-Patel +2 more
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ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2022 Compressive sensing of 2D signals involves three fundamental steps: sparse representation, linear measurement matrix, and recovery of the signal. This paper focuses on analyzing the efficiency of various measurement matrices for compressive sensing of ...
Hepzibah Christinal A +4 more
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