Images are used as data sources for a wide array of technological and scientific applications – in medicine, engineering, geospatial data (GIS) processing, etc. Optical and electron microscopy, static and dynamic x-ray and neutron imaging, system dynamics’ measurements – all of these generally require noise filtering, artefact removal, segmentation analysis, object tracking, and object parameter measurements, etc. Sometimes image restoration is needed especially for damaged and blurred images. In scientific measurements, one often needs to work with images with a low signal-to-noise ratio, which means that specialized methods (often ad hoc) are necessary for non-destructive image filtering. We offer our services in the field of scientific image processing and image restoration, including processing and analysing data derived from images.

For image processing, we use proprietary packages Wolfram Mathematica and Matlab (coupled via Matlink as needed), and open-source tools such as ImageJ and OpenCV, Python, etc.  The methods used for image processing include but are not limited to: noise reduction with luminance anisotropic diffusion and curvature flow, BM3D, (non-)local averaging, Fourier and wavelet filters; Otsu, hysteresis, Chan-Vese, local adaptive segmentation; texture restoration using synthesis and evolution equation methods, as well as our in-house algorithms such as multiscale recursive interrogation filtering.