Pottslab is a Matlab/Java toolbox for the reconstruction of
jump-sparse signals and images using the Potts model (also known as "piecewise constant Mumford-Shah model" or "l0 gradient model").
Applications include denoising of piecewise constant signals, step detection and
segmentation of multichannel image.

— See also the Pick of the Week on View Pottslab - Multilabel segmentation of vectorial data on File Exchange

Application examples

Segmentation of vector-valued images

  • Supports segmentation of vector-valued images (e.g. multispectral images, feature images)
  • Linear complexity in number of color channels
  • Label-free: No label discretization required

Vector-valued segmentation

Left: A natural image; Right: Result using Potts model

Vector-valued segmentation

Texture segmentation using highdimensional curvelet-based feature vectors

Used as segmentation method in

Joint image reconstruction and segmentation

  • Applicable to many imaging operators, e.g. convolution, Radon transform, MRI, PET, MPI: only implementation of proximal mapping reuqired
    – Supports vector-valued data
    – Label-free: Labels need NOT be chosen a-priori


Left: Shepp-Logan phantom; Center: Filtered backprojection from 7 angular projections; Right: Joint reconstruction and segmentation using the Potts model from 7 angular projections

Denoising of jump-sparse/piecewise-constant signals, or step detection/changepoint detection

  • L1 Potts model is robust to noise and to moderately blurred data
  • Fast and exact solver for L1 Potts model
  • Approximative strategies for severely blurred data


Top: Noisy signal; Bottom: Minimizer of Potts functional (ground truth in red)

Used as step detection algorithm in

Usage Instructions

Standalone usage from command line (only image plain image segmentation supported)

  • Call "java -jar pottslab-standalone.jar input output.png gamma" where gamma is a positive real number, e.g. 0.1 (thanks to fxtentacle)

Installation for Matlab (all features usable)


  • Run the script "installPottslab.m", it should set all necessary paths
  • For best performance, increase Java heap space in the Matlab preferences (MATLAB – General – Java heap memory)
  • Run a demo from the Demos folder


Plugins for Image Analysis GUIs

Parts of Pottslab can be used without Matlab as pure Java plugins

  • Icy plugin – an interactive image segmentation plugin based on Pottslab (written by Vasileios Angelopoulos)
  • ImageJ plugin – an ImageJ frontend for Pottslab (written by Michael Kaul)


  • M. Storath, A. Weinmann, J. Frikel, M. Unser.
    "Joint image reconstruction and segmentation using the Potts model"
    Inverse Problems, 2015
  • A. Weinmann, M. Storath. "Iterative Potts and Blake-Zisserman minimization for the recovery of functions with discontinuities from indirect measurements." Proceedings of The Royal Society A, 471(2176), 2015
  • A. Weinmann, M. Storath, L. Demaret.
    "The L1-Potts functional for robust jump-sparse reconstruction"
    SIAM Journal on Numerical Analysis, 2015
  • M. Storath, A. Weinmann.
    "Fast partitioning of vector-valued images"
    SIAM Journal on Imaging Sciences, 2014
  • M. Storath, A. Weinmann, L. Demaret.
    "Jump-sparse and sparse recovery using Potts functionals"
    IEEE Transactions on Signal Processing, 2014
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