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Measurement-Domain Spiral Predictive Coding for Block-Based Image Compressive Sensing
To improve the rate-distortion performance of block-based image compressive sensing and reduce the influence of image edges, this paper proposes a...
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Direct MRI Segmentation from k-Space Data by Iterative Potts Minimization
We consider the problem of image segmentation in magnetic resonance imaging (MRI) directly from k-space measurements as opposed to more standard...
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A multi-level residual reconstruction based image compressed sensing recovery scheme
Traditional image compressed sensing recovery focuses on the research of sparse representation and reweight processing of measurements. However, the...
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The Role of Observers in Computations
John Searle raised the question whether all computation is observer-relative. Indeed, all of the common views of computation, be they semantical,...
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A half-precision compressive sensing framework for end-to-end person re-identification
Compressive sensing (CS) approaches are useful for end-to-end person re-identification (Re-ID) in reducing the overheads of transmitting and storing...
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Iterative Regularization via Dual Diagonal Descent
In the context of linear inverse problems, we propose and study a general iterative regularization method allowing to consider large classes of...
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On the High Complexity of Petri Nets \(\omega \) -Languages
We prove that \(\omega \) -languages of...
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IR Tools: a MATLAB package of iterative regularization methods and large-scale test problems
This paper describes a new MATLAB software package of iterative regularization methods and test problems for large-scale linear inverse problems. The...
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AIR Tools II: algebraic iterative reconstruction methods, improved implementation
We present a MATLAB software package with efficient, robust, and flexible implementations of algebraic iterative reconstruction (AIR) methods for...
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Block compressed sampling of image signals by saliency based adaptive partitioning
In recent years, block compressed sampling (BCS) has emerged as a considerable attractive sampling technology for image acquisition. However, the...
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Block Compressed Sensing Using Random Permutation and Reweighted Sampling for Image Compression Applications
Block compressed sensing (BCS) has great potential in image compression applications for its low storage requirement and low computational...
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Distributed compressed video sensing based on key frame secondary reconstruction
Distributed compressed video sensing scheme combines advantages of compressive sensing and distributed video coding to get better performance, in the...
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Optimization methods for regularization-based ill-posed problems: a survey and a multi-objective framework
Ill-posed problems are widely existed in signal processing. In this paper, we review popular regularization models such as truncated singular value...
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Hybrid wavelet measurement matrices for improving compressive imaging
Compressive sensing principle claims that a compressible signal can be recovered from a small number of random linear measurements. However, the...
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Graph Games and Reactive Synthesis
Graph-based games are an important tool in computer science. They have applications in synthesis, verification, refinement, and far beyond. We review...
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Missing boundary data recovery using Nash games: the Stokes system
We consider the Cauchy-Stokes problem. We use a new method based on Nash game theory to recover the missing velocity and normal stress on some...
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PCA Based Face Recognition on Curvelet Compressive Measurements
This paper proposes an integrated framework to recognize face images using compressive sensing (CS), curvelet transform (CT), and Principal Component...
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CS image reconstruction by novel small length LDPC code
Compressed sensing (CS) is capable of reconstructing the data signal from very small number of measurements. However the reconstructed image quality...
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\(\nu \) acceleration of statistical iterative methods for image restoration
Image restoration problem is an important topic which appears in many different scientific areas. Several solving techniques are available, but...
