Python2 (OpenCV, NumPy) application to refocus blurred images using Wiener deconvolution.
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Updated
Oct 20, 2016 - Python
Python2 (OpenCV, NumPy) application to refocus blurred images using Wiener deconvolution.
Point Spread Function calculations for fluorescence microscopy.
This project deals with blind motion deblurring using a combination of Weiner Deconvolution and Deep Learning techniques to estimate the length and angle parameter of the Point-Spread Function
A Python package for manipulating and correcting variable point spread functions.
“Disparitybased space-variant image deblurring,” Signal Processing: Image Communication, vol. 28, no. 7, pp. 792–808, 2013.
PSF Utilities
Python CLI for batch image deblurring, image restoration, deconvolution, and classical computer vision. Includes Wiener, Richardson-Lucy, Tikhonov, TV-ADMM, and unsupervised Wiener methods; motion/Gaussian/box/custom PSFs; recursive OpenCV/scikit-image processing; color/grayscale support, edge padding, presets, and JSON reports.
Non-generative, physics-informed neural deblurring: deep-unfolded Wiener deconvolution + a Lipschitz-constrained learned denoiser, driven by real camera EXIF/optics -- now with diffraction-limited Airy-disk PSFs, per-RGB-channel chromatic dispersion, and depth-guided spatially variant deconvolution.
非盲图像复原与图像复原
Fitting distributions to discrete stellar profiles in FITS data using LGD.
Python package to create synthetic (fluorescence) microscopy images of (nano)particles and convolution with a point spread function
Physics-based synthetic data and defocus-regression models for fluorescence microscope autofocus: Richards-Wolf vectorial PSF simulation, 14 sample geometries, a full sCMOS/EMCCD sensor model, geometry-invariant focus features, and the classical z-scan baselines to beat.
TOPH is a code for spatially-variable point spread function matching.
Euclid stellar-shape and PSF diagnostic for image-quality assessment, weak-lensing calibration and shape-measurement consistency, using reproducible analysis of observational data and explicit quality limits.
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