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PyWI is a Python image filtering library aimed at removing additive background noise from raster graphics images.


The image filter relies on multiresolution analysis methods (Wavelet transforms) that remove some scales (frequencies) locally in space. These methods are particularly efficient when signal and noise are located at different scales (or frequencies). Optional features improve the SNR ratio when the (clean) signal constitute a single cluster of pixels on the image (e.g. electromagnetic showers produced with Imaging Atmospheric Cherenkov Telescopes). This library is written in Python and is based on the existing Cosmostat tools iSAp (Interactive Sparse Astronomical data analysis Packages).

The PyWI library also contains a dedicated package to optimize the image filter parameters for a given set of images (i.e. to adapt the filter to a specific problem). From a given training set of images (containing pairs of noised and clean images) and a given performance estimator (a function that assess the image filter parameters comparing the cleaned image to the actual clean image), the optimizer can determine the optimal filtering level for each scale.

The PyWI library contains: