albarji/proxTV
Matlab and Python toolbox for fast Total Variation proximity operators
This tool helps scientists and engineers clean up noisy data, such as images, videos, or sensor readings, by smoothing them while preserving important edges or sudden changes. You input your raw, noisy data (like an image) and specify how much smoothing you want. The output is a cleaner, clearer version of your data. This is ideal for researchers, data analysts, or anyone working with signals and measurements who needs to enhance data quality for analysis or visualization.
236 stars. No commits in the last 6 months.
Use this if you need to remove noise from 1D signals, 2D images, 3D video, or higher-dimensional data, and want to achieve a result that is smooth overall but still sharply defines boundaries.
Not ideal if your primary goal is simple blurring, if you require specialized denoising algorithms for specific noise types (e.g., Gaussian only), or if you are working on a Windows operating system.
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236
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Language
C++
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Last pushed
Feb 20, 2020
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