# GammaNoise

### *class* deepinv.physics.GammaNoise(l=1.0)

Bases: [`NoiseModel`](https://deepinv.org/api/stubs/deepinv.physics.NoiseModel.html.md#deepinv.physics.NoiseModel)

Gamma noise $y = \mathcal{G}(\ell, x/\ell)$

Follows the (shape, scale) parameterization of the Gamma distribution,
where the mean is given by $x$ and the variance is given by $x^2/\ell$,
see [https://en.wikipedia.org/wiki/Gamma_distribution](https://en.wikipedia.org/wiki/Gamma_distribution) for more details.

Distribution for modelling speckle noise (e.g. SAR images),
where $\ell>0$ controls the noise level (smaller values correspond to higher noise).

#### WARNING
This noise model does not support the random number generator.

* **Parameters:**
  **l** ([*float*](https://docs.python.org/3.12/library/functions.html#float) *,* [*torch.Tensor*](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor)) – noise level.

#### forward(x, l=None, seed=None, \*\*kwargs)

Adds the noise to measurements x

* **Parameters:**
  * **x** ([*torch.Tensor*](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor)) – measurements
  * **l** (*None* *,* [*float*](https://docs.python.org/3.12/library/functions.html#float) *,* [*torch.Tensor*](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor)) – noise level. If not None, it will overwrite the current noise level.
* **Returns:**
  noisy measurements

<a id="sphx-glr-backref-deepinv-physics-gammanoise"></a>

## Examples using `GammaNoise`:

<div class="sphx-glr-thumbnails">
<!-- thumbnail-parent-div-open --><div class="sphx-glr-thumbcontainer" tooltip="This example shows you how to train a denoiser network in a fully self-supervised way, using noisy images only via the Generalized Recorrupted2Recorrupted (GR2R) loss monroy2025generalized, which exploits knowledge about the noise distribution. You can change the noise distribution by selecting from predefined noise models such as Gaussian, Poisson, and Gamma noise.">![](auto_examples/self-supervised-learning/images/thumb/sphx_glr_demo_r2r_denoising_thumb.png)

[Self-supervised denoising with the Generalized R2R loss.](https://deepinv.org/auto_examples/self-supervised-learning/demo_r2r_denoising.html.md)

  <div class="sphx-glr-thumbnail-title">Self-supervised denoising with the Generalized R2R loss.</div>
</div>
<!-- thumbnail-parent-div-close --></div>