RichardsonLucyRestoration

RichardsonLucyRestoration applies a lightweight Richardson-Lucy deconvolution baseline to a 2D intensity image.

Inputs

• input_image: 2D intensity image.

• psf_image: optional 2D point-spread-function image.

• iterations: number of Richardson-Lucy updates.

• clip: optionally clip output to [0, 1].

Outputs

• output_image: restored float image.

Dependencies and Core Libraries

imageio, NumPy, and the package-local Richardson-Lucy baseline.

Assumptions

This is a lightweight public-library baseline. It is useful for demonstrative deblurring tests but should not replace validated microscope-specific deconvolution workflows.

Minimal Example

from bioimageflow_core import Arguments
from bioimageflow_restoration_tools import RichardsonLucyRestoration

RichardsonLucyRestoration().process_row(
    Arguments(input_image="blurred.tif", iterations=10, output_image="restored.tif")
)

Expected Results

Synthetic blurred fixtures recover sharper peaks than the input under the same array shape.

Failure Modes

Unreadable images, PSF shape mismatches, invalid iteration counts, and write failures raise errors.