PyBM3D

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| *So you want to denoise some images, or maybe shrink inside a projected gradient algorithm?*

This Python package provides an interface for the BM3D denoising strategy which is based on enhanced sparse representations in the transform-domain. The enhancement of the sparsity is achieved by grouping similar 2D image fragments (e.g. blocks) into 3D data arrays. Visit the offical BM3D website <http://www.cs.tut.fi/~foi/GCF-BM3D/>_ for a detailed explanation, benchmark results and other related works.

The core C implementation of BM3D is based on the work <http://www.ipol.im/pub/art/2012/l-bm3d/>_ of Marc Lebrun.

Installation

PyBM3D is supported for Linux and OSX and Python 2.7 and 3.6. Please follow the installation instructions:

1. FFTW3:

   a. Linux: sudo apt-get install libfftw3-dev b. OSX: brew update && brew install fftw

2. pip install pybm3d

Example

+------------------------------------------------------------------------------+ | Denoising a RGB color image | +------------------------------------------------------------------------------+ | .. code:: python | | | | import numpy as np | | import skimage.data | | from skimage.measure import compare_psnr | | | | import pybm3d | | | | | | noise_std_dev = 40 | | img = skimage.data.astronaut() | | noise = np.random.normal(scale=noise_std_dev, | | size=img.shape).astype(img.dtype) | | | | noisy_img = img + noise | | | | out = pybm3d.bm3d.bm3d(noisy_img, noise_std_dev) | | | | noise_psnr = compare_psnr(img, noisy_img) | | out_psnr = compare_psnr(img, out) | | | | print("PSNR of noisy image: ", noise_psnr) | | print("PSNR of reconstructed image: ", out_psnr) | | | +------------------------------------------------------------------------------+

License

This project is released under the terms of the GPL3 license <https://opensource.org/licenses/GPL-3.0>_.

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