Java Code Examples for ij.process.FloatProcessor#getHeight()

private FloatProcessor readMask(String imagePath) {
    if((imagePath != null) && (imagePath.trim().length() > 0)) {
        ImagePlus imp = IJ.openImage(imagePath);
        if(imp != null) {
            // ensure that the maximum value cannot be more than 1.0 !
            FloatProcessor fmask = (FloatProcessor) imp.getProcessor().convertToFloat();
            float min = 0;
            float max = (float) fmask.getMax();
            if(max > 0) {
                for(int x = 0; x < fmask.getWidth(); x++) {
                    for(int y = 0; y < fmask.getHeight(); y++) {
                        fmask.setf(x, y, (fmask.getf(x, y) - min) / (max - min));
                    }
                }
            }
            return fmask;
        }
    }
    return ImageMath.ones(width, height);
}
 

public static FloatProcessor modulo(FloatProcessor mat, float val) {
    FloatProcessor res = new FloatProcessor(mat.getWidth(), mat.getHeight());
    res.setMask(mat.getMask());
    float tmp;
    for (int i = 0, im = mat.getWidth(); i < im; i++) {
        for (int j = 0, jm = mat.getHeight(); j < jm; j++) {
            tmp = mat.getf(i, j) / val;
            res.setf(i, j, mat.getf(i, j) - (((float)((int)tmp)) * val));
        }
    }
    return res;
}
 

public static FloatProcessor relLt(FloatProcessor a, FloatProcessor b) {
    if((a.getWidth() != b.getWidth()) || (a.getHeight()!= b.getHeight())) {
        throw new IllegalArgumentException("Error during evaluation of `a<b` expression! Both operands must be of the same size!");
    }
    FloatProcessor res = new FloatProcessor(a.getWidth(), a.getHeight());
    res.setMask(a.getMask() != null ? a.getMask(): b.getMask());
    for(int x = 0; x < a.getWidth(); x++) {
        for(int y = 0; y < a.getHeight(); y++) {
            res.setf(x, y, ((a.getf(x, y) < b.getf(x, y)) ? 1.0f : 0.0f));
        }
    }
    return res;
}
 

public static FloatProcessor logAnd(FloatProcessor a, FloatProcessor b) {
    if((a.getWidth() != b.getWidth()) || (a.getHeight()!= b.getHeight())) {
        throw new IllegalArgumentException("Error during evaluation of `a&b` expression! Both operands must be of the same size!");
    }
    FloatProcessor res = new FloatProcessor(a.getWidth(), a.getHeight());
    res.setMask(a.getMask() != null ? a.getMask(): b.getMask());
    for(int x = 0; x < a.getWidth(); x++) {
        for(int y = 0; y < a.getHeight(); y++) {
            res.setf(x, y, (((a.getf(x, y) != 0.0f) && (b.getf(x, y) != 0.0f)) ? 1.0f : 0.0f));
        }
    }
    return res;
}
 

private static void processFloat(final FloatProcessor ip,
                                 final float value,
                                 final double min,
                                 final double max) {
    final double scale = max - min;
    final Random rnd = new Random();
    final int n = ip.getWidth() * ip.getHeight();
    for (int i = 0; i < n; ++i) {
        final float v = ip.getf(i);
        if (v == value)
            ip.setf(i, (float) (rnd.nextDouble() * scale + min));
    }
}
 

/**
 * Divide a scalar value by values from an image.
 * 
 * @param val an input value which the input image ({@code fp}) will divide
 * @param fp an input image
 * @return a <strong>new instance</strong> of FloatProcessor: {@mathjax fpv = val / fp}
 */
public static FloatProcessor divide(float val, FloatProcessor fp) {
    FloatProcessor out = new FloatProcessor(fp.getWidth(), fp.getHeight());
    out.setMask(fp.getMask());
    for (int i = 0, im = fp.getWidth(); i < im; i++) {
        for (int j = 0, jm = fp.getHeight(); j < jm; j++) {
            out.setf(i, j, val / fp.getPixelValue(i, j));
        }
    }

    return out;
}
 

public static FloatProcessor logOr(FloatProcessor a, FloatProcessor b) {
    if((a.getWidth() != b.getWidth()) || (a.getHeight()!= b.getHeight())) {
        throw new IllegalArgumentException("Error during evaluation of `a|b` expression! Both operands must be of the same size!");
    }
    FloatProcessor res = new FloatProcessor(a.getWidth(), a.getHeight());
    res.setMask(a.getMask() != null ? a.getMask(): b.getMask());
    for(int x = 0; x < a.getWidth(); x++) {
        for(int y = 0; y < a.getHeight(); y++) {
            res.setf(x, y, (((a.getf(x, y) != 0.0f) || (b.getf(x, y) != 0.0f)) ? 1.0f : 0.0f));
        }
    }
    return res;
}
 

public static FloatProcessor relEq(Double val, FloatProcessor mat) {
    float v = val.floatValue();
    FloatProcessor res = new FloatProcessor(mat.getWidth(), mat.getHeight());
    res.setMask(mat.getMask());
    for(int x = 0; x < mat.getWidth(); x++) {
        for(int y = 0; y < mat.getHeight(); y++) {
            res.setf(x, y, ((mat.getf(x, y) == v) ? 1.0f : 0.0f));
        }
    }
    return res;
}
 

/**
 * Multiply two images.
 * 
 * The images are required to be of the same size.
 *
 * @param fp1 an input image which the other input image ({@code fp2}) will be multiplied with
 * @param fp2 another input image which will be multiplied with {@code fp1}
 * @return a <strong>new instance</strong> of FloatProcessor: {@mathjax fp3 = fp1 * fp2}
 */
public static FloatProcessor multiply(FloatProcessor fp1, FloatProcessor fp2) {
    assert (fp1.getWidth() == fp2.getWidth());
    assert (fp1.getHeight() == fp2.getHeight());

    FloatProcessor out = new FloatProcessor(fp1.getWidth(), fp1.getHeight());
    out.setMask(fp1.getMask() != null ? fp1.getMask(): fp2.getMask());
    for (int i = 0, im = fp1.getWidth(); i < im; i++) {
        for (int j = 0, jm = fp1.getHeight(); j < jm; j++) {
            out.setf(i, j, fp1.getPixelValue(i, j) * fp2.getPixelValue(i, j));
        }
    }

    return out;
}
 

/**
 * Subtract an image from a scalar.
 * 
 * @param val an input value which the input image ({@code fp}) will be subtracted from
 * @param fp an input image
 * @return a <strong>new instance</strong> of FloatProcessor: {@mathjax fpv = val - fp}
 */
public static FloatProcessor subtract(float val, FloatProcessor fp) {
    FloatProcessor out = new FloatProcessor(fp.getWidth(), fp.getHeight());
    out.setMask(fp.getMask());
    for (int i = 0, im = fp.getWidth(); i < im; i++) {
        for (int j = 0, jm = fp.getHeight(); j < jm; j++) {
            out.setf(i, j, val - fp.getPixelValue(i, j));
        }
    }

    return out;
}
 

/**
 * Subtract one image to the other.
 * 
 * The images are required to be of the same size.
 *
 * @param fp1 an input image which the other input image ({@code fp2}) will be subtracted from
 * @param fp2 another input image which will be subtracted from {@code fp1}
 * @return a <strong>new instance</strong> of FloatProcessor: {@mathjax fp3 = fp1 - fp2}
 */
public static FloatProcessor subtract(FloatProcessor fp1, FloatProcessor fp2) {
    assert (fp1.getWidth() == fp2.getWidth());
    assert (fp1.getHeight() == fp2.getHeight());

    FloatProcessor out = new FloatProcessor(fp1.getWidth(), fp1.getHeight());
    out.setMask(fp1.getMask() != null ? fp1.getMask(): fp2.getMask());
    for (int i = 0, im = fp1.getWidth(); i < im; i++) {
        for (int j = 0, jm = fp1.getHeight(); j < jm; j++) {
            out.setf(i, j, fp1.getPixelValue(i, j) - fp2.getPixelValue(i, j));
        }
    }

    return out;
}
 

public static FloatProcessor modulo(float val, FloatProcessor mat) {
    FloatProcessor res = new FloatProcessor(mat.getWidth(), mat.getHeight());
    res.setMask(mat.getMask());
    float tmp;
    for (int i = 0, im = mat.getWidth(); i < im; i++) {
        for (int j = 0, jm = mat.getHeight(); j < jm; j++) {
            tmp = val / mat.getf(i, j);
            res.setf(i, j, val - (((float)((int)tmp)) * mat.getf(i, j)));
        }
    }
    return res;
}
 

/**
 * Add two images.
 * 
 * The images are required to be of the same size.
 *
 * @param fp1 an input image which the other input image ({@code fp2}) will be added to
 * @param fp2 another input image which will be added to {@code fp1}
 * @return a <strong>new instance</strong> of FloatProcessor: {@mathjax fp3 = fp1 + fp2}
 */
public static FloatProcessor add(FloatProcessor fp1, FloatProcessor fp2) {
    assert (fp1.getWidth() == fp2.getWidth());
    assert (fp1.getHeight() == fp2.getHeight());

    FloatProcessor out = new FloatProcessor(fp1.getWidth(), fp1.getHeight());
    out.setMask(fp1.getMask() != null ? fp1.getMask(): fp2.getMask());
    for (int i = 0, im = fp1.getWidth(); i < im; i++) {
        for (int j = 0, jm = fp1.getHeight(); j < jm; j++) {
            out.setf(i, j, fp1.getPixelValue(i, j) + fp2.getPixelValue(i, j));
        }
    }

    return out;
}
 

final static private void processFloat(final FloatProcessor ip, final float value, final double min, final double max) {
	final double scale = max - min;
	final Random rnd = new Random();
	final int n = ip.getWidth() * ip.getHeight();
	for (int i =0; i < n; ++i) {
		final float v = ip.getf(i);
		if (v == value)
			ip.setf(i, (float)(rnd.nextDouble() * scale + min));
	}
}
 

public static FloatProcessor relLt(FloatProcessor mat, Double val) {
    float v = val.floatValue();
    FloatProcessor res = new FloatProcessor(mat.getWidth(), mat.getHeight());
    res.setMask(mat.getMask());
    for(int x = 0; x < mat.getWidth(); x++) {
        for(int y = 0; y < mat.getHeight(); y++) {
            res.setf(x, y, ((mat.getf(x, y) < v) ? 1.0f : 0.0f));
        }
    }
    return res;
}
 

/**
 * Converts the processor to a short (16-bit) label image.
 *
 * @param  renderedImageProcessorWithMasks  processor to convert.
 *
 * @return the converted image.
 */
private static BufferedImage targetToLabelImage(final ImageProcessorWithMasks renderedImageProcessorWithMasks) {

    // convert to 16-bit gray-scale
    if (! (renderedImageProcessorWithMasks.ip instanceof FloatProcessor)) {
        throw new IllegalArgumentException("target must be a " + FloatProcessor.class +
                                           " instance but instead is " +
                                           renderedImageProcessorWithMasks.ip.getClass());
    }

    final FloatProcessor fp = (FloatProcessor) renderedImageProcessorWithMasks.ip;
    final float[] pixels = (float[]) renderedImageProcessorWithMasks.ip.getPixels();
    final short[] labelPixels = new short[pixels.length];
    final short emptyPixel = (short) LabelImageProcessorCache.MAX_LABEL_INTENSITY;

    for (int i = 0; i < pixels.length; i++) {
        if (pixels[i] == 0) {
            // map black to white for DMG
            labelPixels[i] = emptyPixel;
        } else {
            // simple cast is sufficient here because the label sources mapped into this target
            // are all 16-bit values with binary masking
            labelPixels[i] = (short) pixels[i];
        }
    }

    final BufferedImage image = new BufferedImage(fp.getWidth(), fp.getHeight(), BufferedImage.TYPE_USHORT_GRAY);
    final WritableRaster raster = image.getRaster();
    raster.setDataElements(0, 0, fp.getWidth(), fp.getHeight(), labelPixels);

    return image;
}
 

final static private void processFloatNaN(final FloatProcessor ip, final double min, final double max) {
	final double scale = max - min;
	final Random rnd = new Random();
	final int n = ip.getWidth() * ip.getHeight();
	for (int i =0; i < n; ++i) {
		final float v = ip.getf(i);
		if (Float.isNaN(v))
			ip.setf(i, (float)(rnd.nextDouble() * scale + min));
	}
}
 

private boolean isCloseToBorder(FloatProcessor image, Point pos) {
    double x = pos.getX().doubleValue(), y = pos.getY().doubleValue();
    return x < (double)subimageSize || x > (double)(image.getWidth() - subimageSize)
        || y < (double)subimageSize || y > (double)(image.getHeight() - subimageSize);
}
 

/**
 * Apply a {@code mask} to an input {@code image}.
 * 
 * The masking works simply by checking where is a 0 in the mask image and
 * setting the corresponding pixel in the input image to 0 as well. Hence the
 * mask does not have to be binary.
 * 
 * For example let's have the following input image:
 * <pre>
 * {@code
 * 123
 * 456
 * 789}
 * </pre>
 * and the following mask:
 * <pre>
 * {@code
 * 560
 * 804
 * 032}
 * </pre>
 * Then the result of applying the mask is:
 * <pre>
 * {@code
 * 120
 * 406
 * 089}
 * </pre>
 * 
 * @param image an input image
 * @param mask a mask image
 * @return a <strong>new instance</strong> of FloatProcessor that contains the input image after the mask was applied
 */
public static FloatProcessor applyMask(FloatProcessor image, FloatProcessor mask) {
    assert (image.getWidth() == mask.getWidth());
    assert (image.getHeight() == mask.getHeight());

    FloatProcessor result = new FloatProcessor(image.getWidth(), image.getHeight(), (float[]) image.getPixelsCopy(), null);
    for (int x = 0, xm = image.getWidth(); x < xm; x++) {
        for (int y = 0, ym = image.getHeight(); y < ym; y++) {
            if (mask.getf(x, y) == 0.0f) {
                result.setf(x, y, 0.0f);
            }
        }
    }
    
    return result;
}
 

public FloatProcessorT2(final FloatProcessor fp) {
	this(fp.getWidth(), fp.getHeight(), (float[])fp.getPixels(), fp.getColorModel(), fp.getMin(), fp.getMax());
}