The freely available software module below is a 3D LoG filter. It applies a LoG (Laplacian of Gaussian or Mexican Hat) filter to a 2D image or to 3D volume. Here, we have a fast implementation. It is a perfect tool to enhance spots, like spherical particles, in noisy images. This module is easy to tune, only by selecting the standard deviations in X, Y and Z directions.
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.
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.