Results 21 to 30 of about 3,276,837 (200)
Applied Sciences, 2022 Due to the small number of baselines (2–3), the traditional L1 norm compressive sensing method for layover solution in InSAR has poor separation ability and height estimation stability and a long operation time.
Bin Zhang +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
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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
core +2 more sources
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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ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017 With the aim of developing a fast yet accurate algorithm for compressive sensing (CS) reconstruction of natural images, we combine in this paper the merits of two existing categories of CS methods: the structure insights of traditional optimization-based
Jian Zhang, Bernard Ghanem
semanticscholar +1 more source
Nonlinear Compressive Particle Filtering [PDF]
, 2013 Many systems for which compressive sensing is used today are dynamical. The common approach is to neglect the dynamics and see the problem as a sequence of independent problems. This approach has two disadvantages. Firstly, the temporal dependency in the
Ohlsson, Henrik +2 more
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Compressive Sensing-Based Adaptive Active User Detection and Channel Estimation: Massive Access Meets Massive MIMO [PDF]
IEEE Transactions on Signal Processing, 2019 This paper considers massive access in massive multiple-input multiple-output (MIMO) systems and proposes an adaptive active user detection and channel estimation scheme based on compressive sensing.
Malong Ke +4 more
semanticscholar +1 more source