lsst.pipe.tasks.prettyPictureMaker._functors._local_contrast.DiffusionFunction Class Reference
Inheritance diagram for lsst.pipe.tasks.prettyPictureMaker._functors._local_contrast.DiffusionFunction:
Public Member Functions | |
| FloatImagePlane | __call__ (self, FloatImagePlane intensities) |
Static Public Attributes | |
| iterations = Field[int]("number of interations in the diffusion process", default=3) | |
| anisotropy_first | |
| anisotropy_second | |
| anisotropy_third | |
| anisotropy_fourth | |
| regularization = Field[float]("Regularization of coefficients used to detect edges", default=2.94) | |
| variance_threshold | |
| radius_center | |
| radius | |
| first = Field[float](doc="Anisotropic diffusion speed of low-frequency wavelets", default=0.0065) | |
| second | |
| third | |
| fourth | |
| sharpness | |
Detailed Description
Apply anisotropic diffusion processing to enhance image details. Anisotropic diffusion is a multi-scale image processing technique that selectively smooths regions while preserving edges by using spatially varying diffusion coefficients. This implementation uses wavelet-based anisotropic diffusion with configurable anisotropy parameters to control how different frequency components diffuse relative to their gradients. The diffusion process works by: - Applying multiple iterations of gradient-based diffusion - Using different diffusion speeds for low and high frequency wavelets - Controlling diffusion direction via anisotropy parameters - Regularizing coefficients to detect and preserve edges - Modulating response to low-variance regions via variance threshold
Definition at line 34 of file _local_contrast.py.
Member Function Documentation
◆ __call__()
| FloatImagePlane lsst.pipe.tasks.prettyPictureMaker._functors._local_contrast.DiffusionFunction.__call__ | ( | self, | |
| FloatImagePlane | intensities ) |
Apply anisotropic diffusion to the input intensity image.
Parameters
----------
intensities : `FloatImagePlane`
The input intensity image to process.
Returns
-------
result : `FloatImagePlane`
The diffused intensity image with enhanced details.
Notes
-----
This method implements wavelet-based anisotropic diffusion:
1. Multi-scale decomposition: The image is analyzed across multiple
frequency bands using wavelet decomposition.
2. Directional diffusion: Low-frequency wavelets diffuse according to
their own gradient orientation (anisotropy_first) and high-frequency
gradients (anisotropy_second). High-frequency wavelets diffuse
relative to low-frequency gradients (anisotropy_third) and their
own gradients (anisotropy_fourth).
3. Speed control: Diffusion speeds are configured via `first`, `second`,
`third`, and `fourth` parameters for each anisotropy axis.
4. Edge preservation: Regularization prevents diffusion across edges.
Variance threshold modulates response to smooth regions.
5. Scale selection: `radius_center` and `radius` define which scales
are modified, enabling targeted enhancement or denoising.
The diffusion equation is solved iteratively for `iterations` steps,
with the `sharpness` parameter adjusting final detail amplitudes.
Definition at line 100 of file _local_contrast.py.
Member Data Documentation
◆ anisotropy_first
|
static |
Initial value:
= Field[float](
"The diffusion direction of low-frequency wavelets relative to their own gradient orientation",
default=1,
)
Definition at line 52 of file _local_contrast.py.
◆ anisotropy_fourth
|
static |
Initial value:
= Field[float](
"The diffusion direction of high-frequency wavelets relative to their own gradient orientation",
default=1,
)
Definition at line 64 of file _local_contrast.py.
◆ anisotropy_second
|
static |
Initial value:
= Field[float](
"The diffusion direction of low-frequency wavelets relative to the high-frequency gradient.",
default=1,
)
Definition at line 56 of file _local_contrast.py.
◆ anisotropy_third
|
static |
Initial value:
= Field[float](
"The diffusion direction of high-frequency wavelets relative to the low-frequency gradient.",
default=1,
)
Definition at line 60 of file _local_contrast.py.
◆ first
|
static |
Definition at line 86 of file _local_contrast.py.
◆ fourth
|
static |
Initial value:
= Field[float](
doc="High-frequency wavelet diffusion speed along the 4th-order anisotropy axis.", default=-0.2774
)
Definition at line 93 of file _local_contrast.py.
◆ iterations
|
static |
Definition at line 51 of file _local_contrast.py.
◆ radius
|
static |
Initial value:
= Field[float](
doc="The diffusion span defines a radial band (center ± span) for detail modification.", default=5.0
)
Definition at line 83 of file _local_contrast.py.
◆ radius_center
|
static |
Initial value:
= Field[float](
doc=(
"The diffusion scale parameter: zero diffuses fine details (deblurring/denoising), "
"while non-zero values selectively diffuse larger scales to enhance local contrast."
),
default=0.0,
)
Definition at line 76 of file _local_contrast.py.
◆ regularization
|
static |
Definition at line 68 of file _local_contrast.py.
◆ second
|
static |
Initial value:
= Field[float](
doc="Low-frequency wavelet diffusion speed along the 2nd-order anisotropy axis", default=-0.25
)
Definition at line 87 of file _local_contrast.py.
◆ sharpness
|
static |
Initial value:
= Field[float](
doc="Adjusts wavelet detail amplitude. Positive values sharpen, negative values blur.", default=0.0
)
Definition at line 96 of file _local_contrast.py.
◆ third
|
static |
Initial value:
= Field[float](
doc="High-frequency wavelet diffusion speed along the 3rd-order anisotropy axis", default=-0.25
)
Definition at line 90 of file _local_contrast.py.
◆ variance_threshold
|
static |
Initial value:
= Field[float](
doc=(
"The variance threshold modulates the filter's response to low-variance regions, with positive "
" values enhancing local contrast and negative values suppressing noise and blur in those areas"
),
default=0.0,
)
Definition at line 69 of file _local_contrast.py.
The documentation for this class was generated from the following file:
- python/lsst/pipe/tasks/prettyPictureMaker/_functors/_local_contrast.py
Generated on Fri Apr 24 2026 08:38:50 for lsst.pipe.tasks by
1.13.2