destripe 0.1.0

PDHG-based universal stripe-noise removal for images, backed by PyTorch

destripe

PDHG-based universal stripe-noise removal for NumPy images ([H, W] or [H, W, 3]), backed by PyTorch (cpu/cuda).

Features

• Removes vertical and diagonal stripe patterns.
• Supports tiled processing for large images with smooth blending.
• Preserves color by estimating noise from luminance.
• Runs on CPU or CUDA devices.

Install

pip install .

For development:

python -m venv .venv
source .venv/bin/activate
pip install -e .

Quick Start

from destripe import destripe

image = ...  # numpy.ndarray, shape [H, W] or [H, W, 3]

clean = destripe(
    image,
    mu1=0.33,    # smoothing / removal strength
    mu2=0.003,   # stripe penalty (structure protection tradeoff)
    tiles=2,     # n x n grid for tiled processing
    device="cpu" # or "cuda"
)

Parameters

• mu1 (default 0.33): stronger smoothing and stripe suppression as it increases.
• mu2 (default 0.003): larger values enforce stronger stripe extraction but may affect fine structures.
• tiles (default 1): splits image into tiles x tiles; useful for very large inputs.
• device ("cpu" or "cuda"): compute target.

Suggested mu Pairs

• Light, thin stripes: [0.17, 0.003], [0.23, 0.003]
• Typical to strong stripes: [0.33, 0.003], [0.4, 0.007]
• Severe corruption / short stripes: [0.5, 0.017]
• Conservative option: [0.1, 0.0017]

These are starting points, not universal optima.

Test

pytest -q

Reference

• https://github.com/NiklasRottmayer/General-Stripe-Removal