Conventional wisdom and common practice in acquisition and reconstruction of images from
frequency data follow the basic principle of the Nyquist density sampling theory. This …

Implicit neural representations (INRs) have recently advanced numerous vision-related
areas. INR performance depends strongly on the choice of activation function employed in …

压缩感知是建立在矩阵分析, 统计概率论, 拓扑几何, 优化与运筹学, 泛函分析等基础上的一种
全新的信息获取与处理的理论框架. 它基于信号的可压缩性, 通过低维空间, 低分辨率, 欠Nyquist …

The authors present a new approach to building simpler, smaller, and cheaper digital
cameras that can operate efficiently across a broader spectral range than conventional …

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We propose simple and extremely efficient methods for solving the basis pursuit problem
\min{‖u‖_1:Au=f,u∈R^n\}, which is used in compressed sensing. Our methods are based …

Light field photography has gained a significant research interest in the last two decades;
today, commercial light field cameras are widely available. Nevertheless, most existing …

Compressive sensing (CS) is an emerging approach for the acquisition of signals having a
sparse or compressible representation in some basis. While the CS literature has mostly …

We present a framework for solving the large-scale \ell_1-regularized convex minimization
problem: \min‖x‖_1+μf(x). Our approach is based on two powerful algorithmic ideas …

In this thesis, I propose and study an efficient algorithm for solving a class of compressive
sensing problems with total variation regularization. This research is motivated by the need …