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ijp-DEVILS/src/main/java/ch/epfl/biop/DEVIL.java
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DEVIL.java
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package ch.epfl.biop;
import ij.IJ ;
import ij.ImagePlus ;
import ij.ImageStack;
import ij.gui.WaitForUserDialog;
import ij.io.OpenDialog;
import ij.plugin.ChannelSplitter;
import ij.plugin.ImageCalculator;
import ij.plugin.RGBStackMerge;
import ij.plugin.filter.ExtendedPlugInFilter;
import ij.process.ImageProcessor;
//
/*
import loci.formats.*;
//USING LOCI reader
import loci.formats.ChannelSeparator;
import loci.formats.FormatException;
import loci.formats.IFormatReader;
import loci.plugins.util.ImageProcessorReader;
import loci.plugins.util.LociPrefs;
*/
// here is the logic of the plugin
public class DEVIL {
public static void run(int particle_size) {
Boolean testMode = new Boolean(false);
float maxBlur = 40 ;
float min_final = -10 ;
float max_final = 50 ;
// open/read image
//ImagePlus ori_Image = IJ.openImage("D:/Eclipse_workspace/DEVIL/data/fiji_stiched_computeOv20pc-z239.tif");
String imageName = "5z_3c";
ImagePlus ori_Image_ipl = IJ.openImage("I:/000-new_temp/"+imageName+"/"+imageName+".tif");
// get info about the image
// int ori_Image_bitDepth = ori_Image.getBitDepth();
// int[0] = width_Image ; 1 height_Image; 2 channels_Nbr; 3 slices_Nbr; 4 frames_Nbr
int[] ori_Image_Dimensions = ori_Image_ipl.getDimensions();
// split the image in channels
ImagePlus[] ori_Image_Channels_ipl = ChannelSplitter.split(ori_Image_ipl);
ImagePlus[] ori_Image_Channels_processed_ipl = ChannelSplitter.split(ori_Image_ipl);
for (int channel_index = 0 ; channel_index < ori_Image_Dimensions[2] ; channel_index++){
ImagePlus current_Channel_ipl = ori_Image_Channels_ipl[channel_index];
ImageStack current_Ch_istck = current_Channel_ipl.getStack();
ImageStack current_Ch_processed_istck = new ImageStack(ori_Image_Dimensions[0],ori_Image_Dimensions[1],ori_Image_Dimensions[3]);
for (int slice_index = 1 ; slice_index <= ori_Image_Dimensions[3] ; slice_index++){
ImageProcessor current_Channel_Slice = current_Ch_istck.getProcessor(slice_index);
ImageProcessor current_Channel_Slice_processed_ipr = DEVIL.run_ipr(current_Channel_Slice, particle_size, maxBlur, min_final,max_final);
current_Ch_processed_istck.setProcessor(current_Channel_Slice_processed_ipr,slice_index);
if (testMode) IJ.showMessage(" 1 Ch-stack Done");
}
ori_Image_Channels_processed_ipl[channel_index] = new ImagePlus( "ch"+(channel_index+1)+"-processed",current_Ch_processed_istck );
ori_Image_Channels_processed_ipl[channel_index].show();
}
//ImagePlus output = mergeChannels(ori_Image_Channels_processed_ipl , true);
//output.show();
IJ.showMessage("Dataset Done");
}
public static ImageProcessor run_ipr(ImageProcessor ip,int particle_size, float maxBlur,float min_final,float max_final) {
Boolean testMode = new Boolean(false);
WaitForUserDialog WFU = new WaitForUserDialog("look at the image");
// and duplicate
ImagePlus oriImage = new ImagePlus( "ori",ip );
ImagePlus blurImage = new ImagePlus( "blur",ip );
IJ.run(blurImage, "32-bit", "");
// blur the image
IJ.run(blurImage, "Gaussian Blur...", "sigma="+2*particle_size);
if (testMode) {
blurImage.show();
blurImage.setTitle("B");
WFU.show();
}
// normalize using Max
IJ.run(blurImage, "Divide...", "value="+maxBlur);
if (testMode) {
blurImage.show();
blurImage.setTitle("BN");
WFU.show();
}
// divide ORI by blurNorm
ImageCalculator ic = new ImageCalculator();
ImagePlus ori_div_blurNorm = ic.run("Divide create 32-bit", oriImage, blurImage);
if (testMode) {
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("dBN");
WFU.show();
}
// Apply "Square Root"
IJ.run(ori_div_blurNorm, "Square Root", "");
if (testMode) {
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("dBN-SQRT");
WFU.show();
}
// Apply Subtract Background
IJ.run(ori_div_blurNorm, "Subtract Background...", "rolling="+particle_size);
if (testMode){
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("dBN-SQRT-SB");
WFU.show();
}
IJ.setMinAndMax(ori_div_blurNorm , min_final, max_final);
IJ.run(ori_div_blurNorm, "16-bit", "");
if (testMode) {
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("Final");
IJ.showMessage(" 1 image Done");
}
ImageProcessor ori_div_blurNorm_ipr = ori_div_blurNorm.getProcessor();
return ori_div_blurNorm_ipr;
}
/*
* using image Plus
*
*/
/*
public static ImageStack run_Z_stack(ImagePlus ip, int particle_size,float maxBlur,float min_final,float max_final){
Boolean testMode = new Boolean(false);
WaitForUserDialog WFU = new WaitForUserDialog("look at the image");
// int[0] = width_Image ; 1 height_Image; 2 channels_Nbr; 3 slices_Nbr; 4 frames_Nbr
int[] ip_Dimensions = ip.getDimensions();
ImageStack current_Z_stack_processed = new ImageStack(ip_Dimensions[0], ip_Dimensions[1], ip_Dimensions[3]);
ImagePlus current_z_processed = new ImagePlus();
for (int slice_index = 0 ; slice_index < ip_Dimensions[3] ; slice_index++){
// set slice
ip.setZ(slice_index);
ImagePlus current_z = ip.duplicate();
current_z.setTitle("z"+slice_index);
if (testMode){
current_z.show();
WFU.show();
}
current_z_processed = DEVIL.run_Image(current_z, particle_size, maxBlur, min_final,max_final);
current_z_processed.setTitle("z processed");
current_z_processed.show();
ImageProcessor current_z_processed_processor = current_z_processed.getProcessor();
current_Z_stack_processed.setProcessor(current_z_processed_processor, slice_index);
}
if (testMode) IJ.showMessage(" 1 Z-stack Done");
return current_Z_stack_processed;
}
*/
/*
public static ImagePlus run_Image(ImagePlus ip,int particle_size, float maxBlur,float min_final,float max_final) {
Boolean testMode = new Boolean(false);
WaitForUserDialog WFU = new WaitForUserDialog("look at the image");
// and duplicate
ImagePlus oriImage = ip.duplicate();
ImagePlus blurImage = ip.duplicate();
IJ.run(blurImage, "32-bit", "");
// blur the image
IJ.run(blurImage, "Gaussian Blur...", "sigma="+2*particle_size);
if (testMode) {
blurImage.show();
blurImage.setTitle("B");
WFU.show();
}
// normalize using Max
IJ.run(blurImage, "Divide...", "value="+maxBlur);
if (testMode) {
blurImage.show();
blurImage.setTitle("BN");
WFU.show();
}
// divide ORI by blurNorm
ImageCalculator ic = new ImageCalculator();
ImagePlus ori_div_blurNorm = ic.run("Divide create 32-bit", oriImage, blurImage);
if (testMode) {
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("dBN");
WFU.show();
}
// Apply "Square Root"
IJ.run(ori_div_blurNorm, "Square Root", "");
if (testMode) {
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("dBN-SQRT");
WFU.show();
}
// Apply Subtract Background
IJ.run(ori_div_blurNorm, "Subtract Background...", "rolling="+particle_size);
if (testMode){
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("dBN-SQRT-SB");
WFU.show();
}
IJ.setMinAndMax(ori_div_blurNorm , min_final, max_final);
IJ.run(ori_div_blurNorm, "16-bit", "");
if (testMode) {
ori_div_blurNorm.show();
ori_div_blurNorm.setTitle("Final");
IJ.showMessage(" 1 image Done");
}
return ori_div_blurNorm;
}*/
}
/*TO DO LATER
*
* find values for autoscale
// getTheMax of the image
double current_max = currentImage.getProcessor().getStats().max; // works only
// store the value within an array
max_array[slice_index] = current_max ;
// At the end of this loop : every images have been blurred and their respective maximum value measured
// Next : Find the maximum of all the maximum
Arrays.sort(max_array);
*
*/
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