■ CONTENTS Streamlining Data Acquisition: The First Step B Data Alignment B Automated Metabolomics B Data Streaming For Cloud-Based Metabolomics C Feature Analysis C Mass Spectral Annotations C Credentialing D Calculating Mass Measurement Errors D Statistical Analysis: Visualization and Deconvolution E Targeted Validation F Pathway Analysis: Putting Metabolomic Data into a Biological Context F ...

Abstract: The cross-range resolution of forward-looking phase array radar (PAR) is limited by the effective antenna beamwidth since the azimuth echo is the convolution of antenna pattern and targets’ backscattering coefficients. Therefore, deconvolution algorithms are proposed to improve the imaging resolution under the limited antenna beamwidth. However, as a typical inverse problem, deconvolu...

this project describes the steps to process a Bayer raw sensor output image which is noisy, undersampled, and blurred. The final output is a de-noised, de-blurred, and upsampled version of the input image. Some of the in-between steps include lens shading correction, color balancing, demosaicing, color correction, etc. Keywords—raw image ; deblurring ; denoising ; image deconvolution ;

In microscopy, shot noise dominates image formation, which can be modeled as a Poisson process. The Richardson-Lucy method tends to converge slowly for large problems and is not flexible to the addition of nondifferentiable priors. In this project, proximal algorithms like ADMM and Chambolle-Pock are applied to three dimensional deconvolution and are shown to converge faster than Richardson-Lucy.

We present a novel method for blind separation of instruments in polyphonic music based on a non-negative matrix factor 2-D deconvolution algorithm. Using a model which is convolutive in both time and frequency we factorize a spectrogram representation of music into components corresponding to individual instruments. Based on this factorization we separate the instruments using spectrogram mask...

It remains a challenge to simultaneously remove geometric distortion and space-time-varying blur in frames captured through a turbulent atmospheric medium. To solve, or at least reduce these effects, we propose a new scheme to recover a latent image from observed frames by integrating a new variational model and distortion-driven spatialtemporal kernel regression. The proposed scheme first cons...

This paper introduces a novel blind on-line dereverberation algorithm for speech signals based on a natural gradient deconvolution algorithm. Existing blind dereverberation algorithms often employ a structure that performs speech prewhitening using LPC analysis followed by a blind deconvolution step applied to the LPC residual. Here it is shown that better performance can be achieved by respect...

We show that automatic determination of regularization threshold and pre-filtering of 3-D fluorescence microscopic images improves the stability of deconvolution results when using the Linear Least squares Solution or the Maximum a Posteriori method. Doing so, the choice of the regularization parameter much less depends on a priori knowledge of the specimen or skills of the operator. This incre...

This Article is brought to you for free and open access by the Center for Coastal Physical Oceanography at ODU Digital Commons. It has been accepted for inclusion in CCPO Publications by an authorized administrator of ODU Digital Commons. For more information, please contact [email protected]. Repository Citation Pruett, C. D.; Thomas, B. C.; Grosch, C. E.; and Gatski, T. B., "A Temporal A...