Percentile_normalization Plugin for imagej

Introduction

This plugin is developed for SN2N, a self-inspired learning to denoise method for live-cell super-resolution microscopy.

• Preprint: Liying Qu et al. Self-inspired learning to denoise for live-cell super-resolution microscopy, bioRxiv (2024).

• Code avaliable: https://github.com/WeisongZhao/SN2N

• For the ultralow SNR data with ultrahigh baseline signal and a number of hot pixels, we adapted the routinely used percentile normalization before the data generation step to remove the smooth background or hot pixels.

This ImageJ plugin offers real-time execution of Image Percentile Normalization. Users can directly remove the ultra-strong baseline signal before training using this ready-to-use plugin.

How to use

1. Add the Percentile_Norm-0.4.2-SNAPSHOT.jar to your imageJ plugin folder as usual and it will show up in process->Percentile_Normalization:

2. The mainboard and brief introduction to some confusing concepts in it

• the two number(35,657 in this snapshot) under the histogram:

The left one represent the smallest pixel value in the scope(a slice or stack depending on the Mode setting).Accordingly the right one stands for the biggest value in the scope.

• Mode:

this configuration is to specify the scope where we get the x% rank. So the stack scope and slice scope is pretty easy to understand now.

• Set:

The same function as the sliders above.Just another way the get the input argument lower_percentile and the upper_percentile.

• Reset

Undo the changes that happens after the last apply.

• Auto

Just click this buttom, the appropriate manipulation may happens on your image.

• Apply

Only do the apply can we save it in the disk later.

3.Here comes a presentation.