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Anisotropic Nonlocal Means Denoising
Arian Maleki, Manjari Narayan, Richard G. Baraniuk
It has recently been proved that the popular nonlocal means (NLM) denoising algorithm does not optimally denoise images with sharp edges. Its weakness lies in the isotropic nature…
Suboptimality of Nonlocal Means for Images with Sharp Edges
Arian Maleki, Manjari Narayan, Richard G. Baraniuk
We conduct an asymptotic risk analysis of the nonlocal means image denoising algorithm for the Horizon class of images that are piecewise constant with a sharp edge discontinuity.…
A Theory for Optical flow-based Transport on Image Manifolds
Sriram Nagaraj, Aswin C. Sankaranarayanan, Richard G. Baraniuk
An image articulation manifold (IAM) is the collection of images formed when an object is articulated in front of a camera. IAMs arise in a variety of image processing and computer…
Regime Change: Bit-Depth versus Measurement-Rate in Compressive Sensing
Jason N. Laska, Richard G. Baraniuk
The recently introduced compressive sensing (CS) framework enables digital signal acquisition systems to take advantage of signal structures beyond bandlimitedness. Indeed, the num…
Asymptotic Analysis of Complex LASSO via Complex Approximate Message Passing (CAMP)
Arian Maleki, Laura Anitori, Zai Yang +1
Recovering a sparse signal from an undersampled set of random linear measurements is the main problem of interest in compressed sensing. In this paper, we consider the case where b…
Stable Restoration and Separation of Approximately Sparse Signals
Christoph Studer, Richard G. Baraniuk
This paper develops new theory and algorithms to recover signals that are approximately sparse in some general dictionary (i.e., a basis, frame, or over-/incomplete matrix) but cor…