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An ImageJ/Fiji macro which measures quality through two stacks of images assumed to be acquired from two opposite angle of views using gray-level standard deviation.

BM3D is a recent denoising method based on the fact that an image has a locally sparse representation in transform domain. This sparsity is enhanced by grouping similar 2D image patches into 3D groups. In this paper we propose an open-source implementation of the method. We discuss the choice of all parameter methods and confirm their actual optimality. The description of the method is rewritten with a a more transparent notation that in the original paper. A final index gives nonetheless the correspondence between the new notation and the original notation.

It simulates a three-dimensional ground-truth that resembles aspects of a biological object like a spheroid. For each simulated view the signal is attenuated, convolved with an effective PSF, and anisotropically sampled using a Poisson process. 

This Matlab code simulates the noise of the confocal laser scanning microscope depending on the depth in the image stack (serial sections). Using the stack of binary images, it applies different levels of noise in the signal and background parts of the images to simulate confocal images. This is useful for generating "virtual ground truth" images with known values of sample rotation and distortion. 

Mean shift is a filter which acts as edge preserving filter similarly to non local mean or anisotropic diffusion. 

Mean shift can be used for denoising, segmentation or clustering. Two parameters are to be tuned, a spatial size of a patch and a gray level or color distance on which the algorithm is applied.

The phase contrast microscopy segmentation toolbox (PHANTAST) is a collection of open-source algorithms and tools for the processing of phase contrast microscopy (PCM) images. It was developed at University College London's department of Biochemical Engineering and CoMPLEX.

An ImageJ plugin for DEFCoN, the fluorescence spot counter based on fully convolutional neural networks

Align_slices in stack utilized the template matching function cvMatch_Template to do slice registration(alignment) based on a selected landmark.
This function will try to find the landmark or the most similar image pattern in every slice and translate each slice so that the landmark pattern will be the same position throughout the whole stack. It could be used to fix the drift of a time-lapse image stacks.

Source code: link

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.

It implements the template matching function from the OpenCV library. The java interface of OpenCV was done through the javacv library.

This ImageJ plugin contains two functions. The first one is the cvMatch_Template. It implements the template matching function from the OpenCV library.

Deep learning based restoration, with guidelines for training. See also the Fiji plugin.

See more CSBDeep in Knime.

Deep learning for fluorescence image restoration (denoising, deconvolution). Requires training on your data set but the procedure is described.

SciPy is a collection of mathematical algorithms and convenience functions built on the NumPy extension of Python. It adds significant power to the interactive Python session by providing the user with high-level commands and classes for manipulating and visualizing data. With SciPy, an interactive Python session becomes a data-processing and system-prototyping environment. Find more about SciPy here!