Gwyddion

Gwyddion is a modular program for scanning probe microscopy (SPM) data visualization and analysis. It is intended for height fields obtained by AFM, MFM, STM, and SNOM/NSOM techniques, and can also be used for profilometry data, confocal microscopy, and general image analysis.

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• False color visualization. Image representation using user-editable color maps. Supports linear, logarithmic, gradient, edge-detected, local contrast representation, local rank transformation, Canny lines, and zero crossing. Includes OpenGL 3D display with false color or material representation.
• Leveling corrections. Removal of tilts and curvatures from surface data. Includes plane subtraction via points, three-point, facet, polynomial background removal, and default plane. Provides scan line corrections using mean, median, trimmed mean, median difference, polynomial fitting, and leveling along user-defined lines.
• Profile extraction. Extraction of linear profiles along scan axes or arbitrary lines with orthogonal averaging. Supports angularly averaged profiles with automated centering, profiles from multiple images simultaneously, and mean profiles from repeated feature scanning.
• Image filtering. Application of filters including mean, median, trimmed mean, conservative denoise, Kuwahara, minimum, maximum, Gaussian, simple sharpening, k-th rank, and checker pattern removal. Includes sequential alternative filters of opening and closing.
• Statistical distributions and histograms. Calculation of basic quantities Sa, Sq, mean, median, range, skewness, kurtosis, projected area, and surface area. Generates height distributions, angle distributions, 2D slope distribution, 2D angle distribution, Minkowski functionals, area scale graph, and local range.
• Correlation functions and spectral densities. Computation of 1D autocorrelation, 2D autocorrelation, 1D height-height correlation (structure function), 1D power spectral density, radial spectral density, and 2D spectral density. Includes facet orientation analysis and ISO roughness parameter evaluation.
• Grain marking and measurement. Segmentation using threshold-based methods, Otsu's threshold, watershed, logistic regression, or edge detection. Measures boundary, surface area, volume, equivalent ellipses, inscribed and circumscribed circles, Martin diameter, and individual grain properties. Provides grain property statistics, distributions, and correlations.
• Mask operations. Editing via addition, subtraction, and intersection with rectangles and ellipses, growing and shrinking, hole filling, extraction, and inversion. Supports logical operations combination, erosion, dilation, opening, closing, and thinning. Computes Euclidean distance transform.
• Integral transforms. 2D fast Fourier transform (FFT), log-φ FFT representation, 2D continuous wavelet transform (CWT), and 2D discrete wavelet transform (DWT). Enables corrections via DWT denoising, 1D FFT filtering, 2D FFT filtering, 2D frequency splitting, and XY denoising.
• Local data correction. Interpolation of bad spots and masked regions using Laplace or fractal interpolation. Marks global outliers, local outliers, scars (strokes), and inverted lines. Performs mutual cropping of non-intersecting image parts and automatic XY plane rotation correction.
• Deformation corrections. Affine distortion correction, arbitrary polynomial deformation in XY plane, and deformation using a general displacement field. Includes fast scan axis drift correction, extraction of data along a spline path, lattice parameter measurement, step height measurement, and global curvature analysis.
• Magnetic force microscopy (MFM) processing. MFM data recalculation, conversion, simulation, and field shifting. Supports tip modeling, blind estimation, dilation and erosion with certainty map. Performs image merging, immersion, and stitching.
• Artificial data generation. Synthesis using Fourier (frequency space) synthesis, object placement, fibre placement, dynamic spherical particle simulation, dynamic elongated particle simulation, pileup of 3D shapes, predefined patterns (ridges, holes, steps, amphitheatre), columnar film growth simulation, classic ballistic deposition, wave interference, randomized Voronoi/Delaunay lattices, non-equilibrium Ising model, diffusion-limited aggregation, solution of coupled non-linear PDEs, annealing of multi-component mixture, fractional Brownian motion, approximation of phase separated structures, and tiling with avoidance. Includes addition of artificial point and line noise.
• Graph curve analysis. Function fitting, critical dimension determination, manual measurements, curve cutting, alignment, leveling, logscale transformation, peak location, force-distance curve fitting, statistical quantities, and distributions for graph curves. Supports single point spectroscopy and volume force-distance curve fitting.
• XYZ and volume data. Native XYZ data support with regularization to images and rudimentary XYZ processing. Volume data support with extraction of lower-dimensional data, volume force-distance curve fitting, and curve maps representing sets of curves per pixel.

Gwyddion was created by David Nečas (Yeti) and Petr Klapetek. Development began in 2004 as a free tool for scanning probe microscopy data analysis. The program is written primarily in C, with some parts in C++, using the GObject system from GLib. The graphical interface is based on GTK+. The project is hosted at http://gwyddion.net and distributed under the GNU General Public License version 2 or later.

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