import ij.measure.Measurements; //导入依赖的package包/类
/**
 * Identify regions in a binary image likely to correspond to complete TMA cores,
 * based both on size and circularity.
 * @param bp - The binary image to process; 0 should be background, 255 foreground
 * @param minArea - Minimum area of a region to keep (in pixels)
 * @param maxArea - Maximum area of a region to keep (in pixels)
 * @param minCircularity - Minimum circularity of a region to keep.
 * @param labelCores - TRUE if the output should be a labelled image (unique integer value per core), otherwise a binary image will be returned
 * @param polyCentroids - A Polygon to which the centroids of the detected regions will be added (if not null).
 * @return Binary or labelled image showing containing only the regions of bp with shapes & sizes corresponding to likely complete TMA cores.
 */	
private static ImageProcessor identifyGoodCores(ByteProcessor bp, double minArea, double maxArea, double minCircularity, boolean labelCores, Polygon polyCentroids) {
	// Create a binary image of only the roundest structures of approximately the correct area
	bp.setThreshold(127, 512, ImageProcessor.NO_LUT_UPDATE);
	int options = labelCores ? ParticleAnalyzer.SHOW_ROI_MASKS : ParticleAnalyzer.SHOW_MASKS;
	int measurements = Measurements.CENTROID;
	ResultsTable rt = new ResultsTable();
	ParticleAnalyzer pa = new ParticleAnalyzer(options, measurements, rt, minArea, maxArea, minCircularity, 1.0);
	pa.setHideOutputImage(true);
	pa.analyze(new ImagePlus("Temp", bp), bp);
	if (polyCentroids != null) {
		for (int i = 0; i < rt.getCounter(); i++) {
			int x = (int)(rt.getValueAsDouble(ResultsTable.X_CENTROID, i) + .5);
			int y = (int)(rt.getValueAsDouble(ResultsTable.Y_CENTROID, i) + .5);
			polyCentroids.addPoint(x, y);
		}
	}
	return pa.getOutputImage().getProcessor();
}
 

import ij.measure.Measurements; //导入依赖的package包/类
/**
 * @param stats_mode can be 0==stack histogram, 1==each image's histogram, and 2==reference Patch histogram.
 *
 **/
public void set(double saturated, boolean normalize, boolean equalize, int stats_mode, boolean use_full_stack, boolean from_existing_min_and_max, boolean visible_only) throws Exception {
	if (null == reference && 2 == stats_mode) throw new IllegalArgumentException("Need a non-null reference Patch to use 2==stats_mode !");

	this.saturated = saturated;
	set("saturated", saturated);
	this.normalize = normalize;
	set("normalize", normalize);
	this.equalize = equalize;
	set("equalize", equalize);

	this.stats_mode = stats_mode;
	this.use_full_stack = use_full_stack;
	if (from_existing_min_and_max && null != reference) {
		// recreate reference_stats
		ImageProcessor ip = reference.getImageProcessor();
		ip.setMinAndMax(reference.getMin(), reference.getMax());
		reference_stats = ImageStatistics.getStatistics(ip, Measurements.MIN_MAX, reference.getLayer().getParent().getCalibrationCopy());
	}
	this.from_existing_min_and_max = from_existing_min_and_max;
	this.visible_only = visible_only;
}
 

import ij.measure.Measurements; //导入依赖的package包/类
/**
 *  Wrapper calculating average 2D spatial correlation with specified delay in frames 
 */
ImageProcessor average2Dcorr(int nDelay, int nStackSize)
{
	ImageProcessor finalip, ip1,ip2;
	ImageStack crosscorrstack;
	int i,j;
	
	i=1; j=i+nDelay;
	crosscorrstack = new ImageStack(nCorrW,nCorrW);
	
	while(j<=nStackSize)
    {
		imp.setSliceWithoutUpdate(i);
    	ip1 = getFloatversion(imp);
    	imp.setSliceWithoutUpdate(j);
    	ip2 = getFloatversion(imp);

		//subtract average intensity value
    	//in general, something else can be here, like background value
		ip1.subtract(ImageStatistics.getStatistics(ip1,Measurements.MEAN,null).mean);
		ip2.subtract(ImageStatistics.getStatistics(ip2,Measurements.MEAN,null).mean);
				 
			
		if(nCalcMethod==0)
			{finalip = x2D.calcDirectCorrelationImage(ip1,ip2);}
		else
			{finalip = x2D.calcFFTCorrelationImage(ip1, ip2);}
				
		crosscorrstack.addSlice(null, finalip);
		i++; j++;
    }
	//do average projection
	Zproj.setImage(new ImagePlus("", crosscorrstack));
	Zproj.setMethod(ZProjector.AVG_METHOD);
	Zproj.doProjection();
	finalip=Zproj.getProjection().getProcessor();
	
	return finalip;
	
}
 

import ij.measure.Measurements; //导入依赖的package包/类
/**
 * Enhance contrast in low-contrast thumbnail images.
 *
 * @param img
 * @return BufferedImage
 */
public BufferedImage enhanceContrast(BufferedImage img) {
    ImagePlus ip = ManipulationUtils.toImagePlus(PlanarImage.wrapRenderedImage(img), null, border);
    ImageStatistics stats = ImageStatistics.getStatistics(ip.getProcessor(), Measurements.MIN_MAX, null);
    double diff = Math.abs(stats.max - stats.min);
    stats.histMin = Math.max(8, stats.histMin);
    if (diff < 80 && diff > 4) {
        contrastEnhancer.stretchHistogram(ip.getProcessor(), d, stats);
        img = ManipulationUtils.toPlanarImage(ip.getProcessor()).getAsBufferedImage();
    }
    return img;
}
 

import ij.measure.Measurements; //导入依赖的package包/类
protected double max(Object param) {
    RetVal val = arg.eval(param);
    if(val.isMatrix()) {    // FloatProcessor
        return (FloatStatistics.getStatistics((FloatProcessor)val.get(), Measurements.MIN_MAX, null)).max;
    } else if(val.isVector()) {
        return VectorMath.max((Number[])val.get()).doubleValue();
    } else if(val.isValue()) {    // Double
        return ((Double)val.get()).doubleValue();
    }
    throw new FormulaParserException("Variables can be only scalars, vectors, or matrices!");
}
 

import ij.measure.Measurements; //导入依赖的package包/类
protected double min(Object param) {
    RetVal val = arg.eval(param);
    if(val.isMatrix()) {    // FloatProcessor
        return (FloatStatistics.getStatistics((FloatProcessor)val.get(), Measurements.MIN_MAX, null)).min;
    } else if(val.isVector()) {
        return VectorMath.min((Number[])val.get()).doubleValue();
    } else if(val.isValue()) {    // Double
        return ((Double)val.get()).doubleValue();
    }
    throw new FormulaParserException("Variables can be only scalars, vectors, or matrices!");
}
 

import ij.measure.Measurements; //导入依赖的package包/类
protected double std(Object param) {
    RetVal val = arg.eval(param);
    if(val.isMatrix()) {    // FloatProcessor
        return (FloatStatistics.getStatistics((FloatProcessor)val.get(), Measurements.STD_DEV, null)).stdDev;
    } else if(val.isVector()) {
        return VectorMath.stddev((Number[])val.get()).doubleValue();
    } else if(val.isValue()) {    // Double
        return ((Double)val.get()).doubleValue();
    }
    throw new FormulaParserException("Variables can be only scalars, vectors, or matrices!");
}
 

import ij.measure.Measurements; //导入依赖的package包/类
protected double mean(Object param) {
    RetVal val = arg.eval(param);
    if(val.isMatrix()) {    // FloatProcessor
        return (FloatStatistics.getStatistics((FloatProcessor)val.get(), Measurements.MEAN, null)).mean;
    } else if(val.isVector()) {
        return VectorMath.mean((Number[])val.get()).doubleValue();
    } else if(val.isValue()) {    // Double
        return ((Double)val.get()).doubleValue();
    }
    throw new FormulaParserException("Variables can be only scalars, vectors, or matrices!");
}
 

import ij.measure.Measurements; //导入依赖的package包/类
protected double median(Object param) {
    RetVal val = arg.eval(param);
    if(val.isMatrix()) {    // FloatProcessor
        return (FloatStatistics.getStatistics((FloatProcessor)val.get(), Measurements.MEDIAN, null)).median;
    } else if(val.isVector()) {
        return VectorMath.median((Number[])val.get()).doubleValue();
    } else if(val.isValue()) {    // Double
        return ((Double)val.get()).doubleValue();
    }
    throw new FormulaParserException("Variables can be only scalars, vectors, or matrices!");
}
 

import ij.measure.Measurements; //导入依赖的package包/类
private final float[] calculateSummary(ResultsTable rt, ImagePlus image) {
        float[] summaries = null;
        if(defaultAnalysisOptions.isMeasureRgb()) {
                summaries = new float[RESULTS_COLUMNS.length+11]; //9 for RGB and 2 for area & %area
        }
        else {
                summaries = new float[RESULTS_COLUMNS.length+2];
        }
        
        float areaSum = calculateSum(rt.getColumn(RESULTS_COLUMNS[ResultsTable.AREA]));
        
        Calibration calibration = image.getCalibration();
        ImageProcessor ip = image.getProcessor();
        Rectangle r = ip.getRoi();
        ImageProcessor mask = ip.getMask();
        double totalArea = 0;
        if(mask != null) {
                totalArea = ImageStatistics.getStatistics(ip, Measurements.AREA, calibration).area;
        }
        else {
                totalArea = r.width*calibration.pixelWidth*r.height*calibration.pixelHeight;
        }
        
        float pctArea = areaSum*100.0f/(float)totalArea;
        
        summaries[0] = areaSum;
        summaries[1] = new BigDecimal(pctArea).round(MC).floatValue();
        
        for(int i=0; i < RESULTS_COLUMNS.length; i++) {
                float[] columnData = rt.getColumn(RESULTS_COLUMNS[i]);
                float sumAvg = calculateSumAverage(columnData);
                summaries[i+2] = new BigDecimal(sumAvg).round(MC).floatValue();
        }
        
        return summaries;
}
 

import ij.measure.Measurements; //导入依赖的package包/类
/**
 * Realiza uma analise de particulas na imagem do bullet. Estes resultados serao analizados juntamente com as outras imagens de bullets de alternativas. 
 * @param bi
 * @return
 */
protected ResultsTable particleAnaylis(BufferedImage bi) {

	// wrapper de imagem do ImageJ para analise
	ImagePlus ip = new ImagePlus("bullet", bi);

	// prepara imagem para analise
	contrastImageThresholds(ip, JazzOMRImageParser.THRESHOLD_HUANG);

	// cria tabela de resultados
	ResultsTable rt = new ResultsTable();

	// determina parametros de analise
	double area = bi.getHeight() * bi.getWidth();
	double minArea = area * bulletMinAreaFactor;
	double maxArea = area * bulletMaxAreaFactor;

	/*
	private double bulletMinAreaFactor = 0.10;
	private double bulletMaxAreaFactor = 0.95;
	private double bulletMinCirc = 0.30;
	*/
	// cria analizador de particulas para bullets
	ParticleAnalyzer jpa = new ParticleAnalyzer(0, Measurements.AREA+Measurements.CIRCULARITY, rt, minArea, maxArea, bulletMinCirc, JazzOMRImageParser.MAX_CIRCULARITY);

	// executa analise
	jpa.analyze(ip);

	// testa se foram encotradas particulas
	//boolean checked = rt.getCounter() > 0;
	
	//imageDocLogger.logBullet(checked,bi,rt);
	//if(log.isDebugEnabled()){
	//}
	
	return rt;

}
 

import ij.measure.Measurements; //导入依赖的package包/类
/**
 * Realiza uma analise de particulas na imagem do bullet. Estes resultados serao analizados juntamente com as outras imagens de bullets de alternativas.
 * 
 * @param bi
 * @return
 */
private ResultsTable particleAnaylis(BufferedImage bi) {

	// wrapper de imagem do ImageJ para analise
	ImagePlus ip = new ImagePlus("bullet", bi);

	// prepara imagem para analise
	contrastImageThresholds(ip, JazzOMRImageParser.THRESHOLD_HUANG);

	// cria tabela de resultados
	ResultsTable rt = new ResultsTable();

	// determina parametros de analise
	double area = bi.getHeight() * bi.getWidth();
	double minArea = area * bulletMinAreaFactor;
	double maxArea = area * bulletMaxAreaFactor;

	/*
	 * private double bulletMinAreaFactor = 0.10; private double bulletMaxAreaFactor = 0.95; private double bulletMinCirc = 0.30;
	 */
	// cria analizador de particulas para bullets
	ParticleAnalyzer jpa = new ParticleAnalyzer(0, Measurements.AREA + Measurements.CIRCULARITY, rt, minArea, maxArea, bulletMinCirc, JazzOMRImageParser.MAX_CIRCULARITY);

	// executa analise
	jpa.analyze(ip);

	// testa se foram encotradas particulas
	boolean checked = rt.getCounter() > 0;

	if (log.isDebugEnabled()) {
		imageDocLogger.logBullet(checked, bi, rt);
	}

	return rt;

}
 

import ij.measure.Measurements; //导入依赖的package包/类
public void run(String arg) {
	ImagePlus current = IJ.getImage();
	Analyzer.setMeasurement(Measurements.LABELS, true);
	for (int i=0; i<current.getStackSize(); i++) {
		current.setSlice(i+1);
		IJ.showProgress(i+1, current.getStackSize());
		IJ.run(current, "Measure", "");	
	}
}
 

import ij.measure.Measurements; //导入依赖的package包/类
private void updateMinAndMax(ImagePlus imp, double[] limits)
{
	ImageStack stack = imp.getImageStack();
	for (int slice = 1; slice <= stack.getSize(); slice++)
	{
		ImageStatistics stats = ImageStatistics.getStatistics(stack.getProcessor(slice), Measurements.MIN_MAX,
				null);
		if (limits[0] > stats.min)
			limits[0] = stats.min;
		if (limits[1] < stats.max)
			limits[1] = stats.max;
	}		
}
 

import ij.measure.Measurements; //导入依赖的package包/类
public ContrastEnhancerWrapper(final Patch reference) {
	this.reference = reference;
	if (null != reference) {
		ImageProcessor ip = reference.getImageProcessor();
		reference_stats = ImageStatistics.getStatistics(ip, Measurements.MIN_MAX, reference.getLayer().getParent().getCalibrationCopy());
	}
}
 

import ij.measure.Measurements; //导入依赖的package包/类
@Override
public ImageProcessor process(ImageProcessor ip) {
	// Will not alter ip, no need to duplicate
	new ContrastEnhancer().stretchHistogram(ip, s, ImageStatistics.getStatistics(ip, Measurements.MIN_MAX, null));
	return ip;
}