BM3D

class deepinv.models.BM3D

Bases: Denoiser

BM3D denoiser.

The BM3D denoiser was introduced by Dabov et al.[1].

Note

Unlike other denoisers from the library, this denoiser is applied sequentially to each noisy image in the batch (no parallelization). Furthermore, it does not support backpropagation.

Warning

This module wraps the BM3D denoiser from the BM3D python package. It can be installed with pip install bm3d.

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References:

[1]

Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian. Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Transactions on image processing, 16(8):2080–2095, 2007.

forward(x, sigma, **kwargs)

Run the denoiser on image with noise level \(\sigma\).

Parameters:

• x (torch.Tensor) – noisy image

• sigma (float) – noise level

Examples using BM3D:

A tour of DeepInv’s denoisers

A tour of DeepInv's denoisers