Abstract: Blind deconvolution is the recovery of a sharp version of a blurred image when the blur kernel is unknown. Recent algorithms have afforded dramatic progress, yet many aspects of the problem ...
Multichannel Statistical Broadband Wavelet Deconvolution for Improving Resolution of Seismic Signals
Abstract: Many popular deconvolution methods based on Robinson's convolutional model have played an important role in improving the temporal resolution of seismic data. However, the outcomes of ...
A new publication from Opto-Electronic Advances, 10.29026/oes.2024.230020 discusses revolutionizing OCT imaging. Deconvolution, an essential method widely employed in various optical imaging ...
Deconvolution is a quantitative approach that uses the picture as an estimate of the real specimen intensity and conducts the mathematical inverse of the imaging process to generate an improved ...
Selecting the right deconvolution method to analyze the composition of complex mixtures of cells just got easier. Researchers derived clear guidelines scientists can use to determine the deconvolution ...
Copyright 2025 The Associated Press. All Rights Reserved. Copyright 2025 The Associated Press. All Rights Reserved. Share NORTHAMPTON, Mass., Oct. 29, 2020 ...
The growing use of intact protein mass analysis, top-down proteomics, and native mass spectrometry have created a need for improved data analysis pipelines for deconvolution of electrospray (ESI) mass ...
Reveal the hidden structures in your sample using cellSens imaging software, which includes a wide range of powerful deconvolution tools. Real-time deconvolution can be applied to live images using ...
Deconvolution is a computational technique of increasing the resolution and SNR (signal to noise ratio) of images captured on an imaging system. Its use existed before the extensive use of confocal ...
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