443 lines
16 KiB
Java
Executable File
443 lines
16 KiB
Java
Executable File
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import ij.*;
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import ij.process.*;
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import ij.gui.*;
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import ij.measure.*;
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import ij.plugin.ContrastEnhancer;
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import java.awt.*;
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import java.util.*;
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import ij.plugin.filter.PlugInFilter;
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/**
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This class implements the Process/FFT/bandpass Filter command. It started out as
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Joachim Walter's FFT Filter plugin at "http://rsb.info.nih.gov/ij/plugins/fft-filter.html".
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2001/10/29: First Version (JW)
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2003/02/06: 1st bugfix (works in macros/plugins, works on stacks, overwrites image(=>filter)) (JW)
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2003/07/03: integrated into ImageJ, added "Display Filter" option (WSR)
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2007/03/26: 2nd bugfix (Fixed incorrect calculation of filter from structure sizes, which caused
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the real structure sizes to be wrong by a factor of 0.75 to 1.5 depending on the image size.)
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*/
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public class BandpassFilter implements PlugInFilter, Measurements {
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private ImagePlus imp;
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private String arg;
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private static int filterIndex = 1;
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private FHT fht;
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private int slice;
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private int stackSize = 1;
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public static double filterLargeDia = 40.0;
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public static double filterSmallDia = 3.0;
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public static int choiceIndex = 0;
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public static String[] choices = {"None","Horizontal","Vertical"};
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public static String choiceDia = choices[0];
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public static double toleranceDia = 5.0;
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public static boolean doScalingDia = true;
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public static boolean saturateDia = true;
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public static boolean displayFilter;
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public static boolean processStack;
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public int setup(String arg, ImagePlus imp) {
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this.arg = arg;
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this.imp = imp;
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if (imp==null)
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{IJ.noImage(); return DONE;}
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stackSize = imp.getStackSize();
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fht = (FHT)imp.getProperty("FHT");
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if (fht!=null) {
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IJ.error("FFT Filter", "Spatial domain image required");
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return DONE;
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}
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//if (!showBandpassDialog(imp))
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// return DONE;
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//else
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return processStack?DOES_ALL+DOES_STACKS:DOES_ALL;
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}
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public void run(ImageProcessor ip) {
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slice++;
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filter(ip);
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}
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void filter(ImageProcessor ip) {
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ImageProcessor ip2 = ip;
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if (ip2 instanceof ColorProcessor) {
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showStatus("Extracting brightness");
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ip2 = ((ColorProcessor)ip2).getBrightness();
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}
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Rectangle roiRect = ip2.getRoi();
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int maxN = Math.max(roiRect.width, roiRect.height);
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double sharpness = (100.0 - toleranceDia) / 100.0;
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boolean doScaling = doScalingDia;
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boolean saturate = saturateDia;
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IJ.showProgress(1,20);
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/* tile mirrored image to power of 2 size
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first determine smallest power 2 >= 1.5 * image width/height
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factor of 1.5 to avoid wrap-around effects of Fourier Trafo */
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int i=2;
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while(i<1.5 * maxN) i *= 2;
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// Calculate the inverse of the 1/e frequencies for large and small structures.
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double filterLarge = 2.0*filterLargeDia / (double)i;
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double filterSmall = 2.0*filterSmallDia / (double)i;
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// fit image into power of 2 size
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Rectangle fitRect = new Rectangle();
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fitRect.x = (int) Math.round( (i - roiRect.width) / 2.0 );
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fitRect.y = (int) Math.round( (i - roiRect.height) / 2.0 );
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fitRect.width = roiRect.width;
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fitRect.height = roiRect.height;
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// put image (ROI) into power 2 size image
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// mirroring to avoid wrap around effects
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showStatus("Pad to "+i+"x"+i);
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ip2 = tileMirror(ip2, i, i, fitRect.x, fitRect.y);
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IJ.showProgress(2,20);
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// transform forward
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showStatus(i+"x"+i+" forward transform");
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FHT fht = new FHT(ip2);
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fht.setShowProgress(false);
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fht.transform();
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System.gc();
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IJ.showProgress(9,20);
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//new ImagePlus("after fht",ip2.crop()).show();
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// filter out large and small structures
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showStatus("Filter in frequency domain");
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filterLargeSmall(fht, filterLarge, filterSmall, choiceIndex, sharpness);
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//new ImagePlus("filter",ip2.crop()).show();
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IJ.showProgress(11,20);
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// transform backward
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showStatus("Inverse transform");
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fht.inverseTransform();
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IJ.showProgress(19,20);
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//new ImagePlus("after inverse",ip2).show();
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// crop to original size and do scaling if selected
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showStatus("Crop and convert to original type");
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fht.setRoi(fitRect);
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ip2 = fht.crop();
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if (doScaling) {
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ImagePlus imp2 = new ImagePlus(imp.getTitle()+"-filtered", ip2);
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new ContrastEnhancer().stretchHistogram(imp2, saturate?1.0:0.0);
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ip2 = imp2.getProcessor();
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}
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// convert back to original data type
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int bitDepth = imp.getBitDepth();
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switch (bitDepth) {
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case 8: ip2 = ip2.convertToByte(doScaling); break;
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case 16: ip2 = ip2.convertToShort(doScaling); break;
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case 24:
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ip.snapshot();
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showStatus("Setting brightness");
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((ColorProcessor)ip).setBrightness((FloatProcessor)ip2);
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break;
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case 32: break;
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}
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// copy filtered image back into original image
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if (bitDepth!=24) {
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ip.snapshot();
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ip.copyBits(ip2, roiRect.x, roiRect.y, Blitter.COPY);
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}
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ip.resetMinAndMax();
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System.gc();
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IJ.showProgress(20,20);
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}
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void showStatus(String msg) {
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if (stackSize>1 && processStack)
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IJ.showStatus("FFT Filter: "+slice+"/"+stackSize);
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else
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IJ.showStatus(msg);
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}
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/** Puts imageprocessor (ROI) into a new imageprocessor of size width x height y at position (x,y).
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The image is mirrored around its edges to avoid wrap around effects of the FFT. */
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ImageProcessor tileMirror(ImageProcessor ip, int width, int height, int x, int y) {
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if (x < 0 || x > (width -1) || y < 0 || y > (height -1)) {
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IJ.error("Image to be tiled is out of bounds.");
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return null;
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}
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ImageProcessor ipout = ip.createProcessor(width, height);
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ImageProcessor ip2 = ip.crop();
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int w2 = ip2.getWidth();
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int h2 = ip2.getHeight();
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//how many times does ip2 fit into ipout?
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int i1 = (int) Math.ceil(x / (double) w2);
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int i2 = (int) Math.ceil( (width - x) / (double) w2);
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int j1 = (int) Math.ceil(y / (double) h2);
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int j2 = (int) Math.ceil( (height - y) / (double) h2);
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//tile
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if ( (i1%2) > 0.5)
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ip2.flipHorizontal();
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if ( (j1%2) > 0.5)
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ip2.flipVertical();
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for (int i=-i1; i<i2; i += 2) {
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for (int j=-j1; j<j2; j += 2) {
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ipout.insert(ip2, x-i*w2, y-j*h2);
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}
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}
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ip2.flipHorizontal();
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for (int i=-i1+1; i<i2; i += 2) {
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for (int j=-j1; j<j2; j += 2) {
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ipout.insert(ip2, x-i*w2, y-j*h2);
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}
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}
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ip2.flipVertical();
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for (int i=-i1+1; i<i2; i += 2) {
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for (int j=-j1+1; j<j2; j += 2) {
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ipout.insert(ip2, x-i*w2, y-j*h2);
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}
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}
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ip2.flipHorizontal();
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for (int i=-i1; i<i2; i += 2) {
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for (int j=-j1+1; j<j2; j += 2) {
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ipout.insert(ip2, x-i*w2, y-j*h2);
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}
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}
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return ipout;
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}
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/*
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filterLarge: down to which size are large structures suppressed?
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filterSmall: up to which size are small structures suppressed?
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filterLarge and filterSmall are given as fraction of the image size
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in the original (untransformed) image.
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stripesHorVert: filter out: 0) nothing more 1) horizontal 2) vertical stripes
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(i.e. frequencies with x=0 / y=0)
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scaleStripes: width of the stripe filter, same unit as filterLarge
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*/
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void filterLargeSmall(ImageProcessor ip, double filterLarge, double filterSmall, int stripesHorVert, double scaleStripes) {
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int maxN = ip.getWidth();
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float[] fht = (float[])ip.getPixels();
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float[] filter = new float[maxN*maxN];
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for (int i=0; i<maxN*maxN; i++)
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filter[i]=1f;
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int row;
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int backrow;
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float rowFactLarge;
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float rowFactSmall;
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int col;
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int backcol;
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float factor;
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float colFactLarge;
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float colFactSmall;
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float factStripes;
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// calculate factor in exponent of Gaussian from filterLarge / filterSmall
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double scaleLarge = filterLarge*filterLarge;
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double scaleSmall = filterSmall*filterSmall;
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scaleStripes = scaleStripes*scaleStripes;
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//float FactStripes;
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// loop over rows
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for (int j=1; j<maxN/2; j++) {
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row = j * maxN;
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backrow = (maxN-j)*maxN;
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rowFactLarge = (float) Math.exp(-(j*j) * scaleLarge);
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rowFactSmall = (float) Math.exp(-(j*j) * scaleSmall);
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// loop over columns
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for (col=1; col<maxN/2; col++){
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backcol = maxN-col;
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colFactLarge = (float) Math.exp(- (col*col) * scaleLarge);
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colFactSmall = (float) Math.exp(- (col*col) * scaleSmall);
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factor = (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall;
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switch (stripesHorVert) {
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case 1: factor *= (1 - (float) Math.exp(- (col*col) * scaleStripes)); break;// hor stripes
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case 2: factor *= (1 - (float) Math.exp(- (j*j) * scaleStripes)); // vert stripes
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}
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fht[col+row] *= factor;
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fht[col+backrow] *= factor;
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fht[backcol+row] *= factor;
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fht[backcol+backrow] *= factor;
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filter[col+row] *= factor;
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filter[col+backrow] *= factor;
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filter[backcol+row] *= factor;
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filter[backcol+backrow] *= factor;
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}
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}
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//process meeting points (maxN/2,0) , (0,maxN/2), and (maxN/2,maxN/2)
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int rowmid = maxN * (maxN/2);
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rowFactLarge = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleLarge);
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rowFactSmall = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleSmall);
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factStripes = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleStripes);
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fht[maxN/2] *= (1 - rowFactLarge) * rowFactSmall; // (maxN/2,0)
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fht[rowmid] *= (1 - rowFactLarge) * rowFactSmall; // (0,maxN/2)
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fht[maxN/2 + rowmid] *= (1 - rowFactLarge*rowFactLarge) * rowFactSmall*rowFactSmall; // (maxN/2,maxN/2)
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filter[maxN/2] *= (1 - rowFactLarge) * rowFactSmall; // (maxN/2,0)
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filter[rowmid] *= (1 - rowFactLarge) * rowFactSmall; // (0,maxN/2)
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filter[maxN/2 + rowmid] *= (1 - rowFactLarge*rowFactLarge) * rowFactSmall*rowFactSmall; // (maxN/2,maxN/2)
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switch (stripesHorVert) {
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case 1: fht[maxN/2] *= (1 - factStripes);
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fht[rowmid] = 0;
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fht[maxN/2 + rowmid] *= (1 - factStripes);
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filter[maxN/2] *= (1 - factStripes);
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filter[rowmid] = 0;
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filter[maxN/2 + rowmid] *= (1 - factStripes);
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break; // hor stripes
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case 2: fht[maxN/2] = 0;
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fht[rowmid] *= (1 - factStripes);
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fht[maxN/2 + rowmid] *= (1 - factStripes);
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filter[maxN/2] = 0;
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filter[rowmid] *= (1 - factStripes);
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filter[maxN/2 + rowmid] *= (1 - factStripes);
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break; // vert stripes
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}
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//loop along row 0 and maxN/2
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rowFactLarge = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleLarge);
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rowFactSmall = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleSmall);
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for (col=1; col<maxN/2; col++){
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backcol = maxN-col;
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colFactLarge = (float) Math.exp(- (col*col) * scaleLarge);
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colFactSmall = (float) Math.exp(- (col*col) * scaleSmall);
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switch (stripesHorVert) {
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case 0:
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fht[col] *= (1 - colFactLarge) * colFactSmall;
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fht[backcol] *= (1 - colFactLarge) * colFactSmall;
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fht[col+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall;
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fht[backcol+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall;
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filter[col] *= (1 - colFactLarge) * colFactSmall;
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filter[backcol] *= (1 - colFactLarge) * colFactSmall;
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filter[col+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall;
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filter[backcol+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall;
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break;
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case 1:
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factStripes = (float) Math.exp(- (col*col) * scaleStripes);
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fht[col] *= (1 - colFactLarge) * colFactSmall * (1 - factStripes);
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fht[backcol] *= (1 - colFactLarge) * colFactSmall * (1 - factStripes);
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fht[col+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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fht[backcol+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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filter[col] *= (1 - colFactLarge) * colFactSmall * (1 - factStripes);
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filter[backcol] *= (1 - colFactLarge) * colFactSmall * (1 - factStripes);
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filter[col+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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filter[backcol+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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break;
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case 2:
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factStripes = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleStripes);
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fht[col] = 0;
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fht[backcol] = 0;
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fht[col+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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fht[backcol+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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filter[col] = 0;
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filter[backcol] = 0;
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filter[col+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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filter[backcol+rowmid] *= (1 - colFactLarge*rowFactLarge) * colFactSmall*rowFactSmall * (1 - factStripes);
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}
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}
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// loop along column 0 and maxN/2
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colFactLarge = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleLarge);
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colFactSmall = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleSmall);
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for (int j=1; j<maxN/2; j++) {
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row = j * maxN;
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backrow = (maxN-j)*maxN;
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rowFactLarge = (float) Math.exp(- (j*j) * scaleLarge);
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rowFactSmall = (float) Math.exp(- (j*j) * scaleSmall);
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switch (stripesHorVert) {
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case 0:
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fht[row] *= (1 - rowFactLarge) * rowFactSmall;
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fht[backrow] *= (1 - rowFactLarge) * rowFactSmall;
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fht[row+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall;
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fht[backrow+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall;
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filter[row] *= (1 - rowFactLarge) * rowFactSmall;
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filter[backrow] *= (1 - rowFactLarge) * rowFactSmall;
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filter[row+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall;
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filter[backrow+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall;
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break;
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case 1:
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factStripes = (float) Math.exp(- (maxN/2)*(maxN/2) * scaleStripes);
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fht[row] = 0;
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fht[backrow] = 0;
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fht[row+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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fht[backrow+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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filter[row] = 0;
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filter[backrow] = 0;
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filter[row+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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filter[backrow+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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break;
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case 2:
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factStripes = (float) Math.exp(- (j*j) * scaleStripes);
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fht[row] *= (1 - rowFactLarge) * rowFactSmall * (1 - factStripes);
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fht[backrow] *= (1 - rowFactLarge) * rowFactSmall * (1 - factStripes);
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fht[row+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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fht[backrow+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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filter[row] *= (1 - rowFactLarge) * rowFactSmall * (1 - factStripes);
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filter[backrow] *= (1 - rowFactLarge) * rowFactSmall * (1 - factStripes);
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filter[row+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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filter[backrow+maxN/2] *= (1 - rowFactLarge*colFactLarge) * rowFactSmall*colFactSmall * (1 - factStripes);
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}
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}
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if (displayFilter && slice==1) {
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FHT f = new FHT(new FloatProcessor(maxN, maxN, filter, null));
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f.swapQuadrants();
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new ImagePlus("Filter", f).show();
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}
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}
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boolean showBandpassDialog(ImagePlus imp) {
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GenericDialog gd = new GenericDialog("FFT Bandpass Filter");
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gd.addNumericField("Filter_Large Structures Down to", filterLargeDia, 0, 4, "pixels");
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gd.addNumericField("Filter_Small Structures Up to", filterSmallDia, 0, 4, "pixels");
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gd.addChoice("Suppress Stripes:", choices, choiceDia);
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gd.addNumericField("Tolerance of Direction:", toleranceDia, 0, 2, "%");
|
|
gd.addCheckbox("Autoscale After Filtering", doScalingDia);
|
|
gd.addCheckbox("Saturate Image when Autoscaling", saturateDia);
|
|
gd.addCheckbox("Display Filter", displayFilter);
|
|
if (stackSize>1)
|
|
gd.addCheckbox("Process Entire Stack", processStack);
|
|
gd.showDialog();
|
|
if(gd.wasCanceled())
|
|
return false;
|
|
if(gd.invalidNumber()) {
|
|
IJ.error("Error", "Invalid input number");
|
|
return false;
|
|
}
|
|
filterLargeDia = gd.getNextNumber();
|
|
filterSmallDia = gd.getNextNumber();
|
|
choiceIndex = gd.getNextChoiceIndex();
|
|
choiceDia = choices[choiceIndex];
|
|
toleranceDia = gd.getNextNumber();
|
|
doScalingDia = gd.getNextBoolean();
|
|
saturateDia = gd.getNextBoolean();
|
|
displayFilter = gd.getNextBoolean();
|
|
if (stackSize>1)
|
|
processStack = gd.getNextBoolean();
|
|
return true;
|
|
}
|
|
|
|
}
|