Examples of javax.media.jai.Histogram

javax.media.jai.Histogram
This class represents a histogram accumulated from a RenderedImage.
A "bin" is a container, where each element stores the total number of pixel samples of an image whose values lie within a given range. A histogram of an image consists of a list of such bins whose range does not overlap with each other (mutually exclusive). For an image that has multiple samples per pixel (multi-banded images), a separate list of bins represents each individual band.
A "low-value" specifies the lowest inclusive pixel value to be checked, and a "high-value" specifies the highest exclusive pixel value to be checked. Therefore, the width of a bin (binWidth) is determined by (highValue - lowValue) / numberOfBins. The range of bin i is defined as from lowValue + i * binWidth inclusive to lowValue + (i + 1) * binWidth exclusive.
The image may have any data type. Its histogram may be accumulated over the entire image, or over a specific region-of-interest (ROI) within the image's bounds. Furthermore, the horizontal and vertical subsampling factors specify the rate of sampling in the two directions, so that only every nth pixel will be counted. This allows the accuracy of the histogram to be traded for the speed of the computation. Of course a subsampling rate of 1 means every pixel will be counted.
The "Histogram" operator generates the histogram data of an image and uses this object to store the final pixel counts. The operator returns an instance of this class when a request is made via the getProperty method for the "histogram" property. The actual bins may be obtained by calling the getBins method. @see ROI @see javax.media.jai.operator.HistogramDescriptor

    // Create the histogram
    //
    // /////////////////////////////////////////////////////////////////////
    final PlanarImage histogramImage = JAI.create("histogram", pb,
        new RenderingHints(JAI.KEY_TILE_CACHE, null));
    final Histogram hist = (Histogram) histogramImage
        .getProperty("histogram");
    pb.removeParameters();
    pb.removeSources();


    // /////////////////////////////////////////////////////////////////////
    //
    // Write things
    //
    // /////////////////////////////////////////////////////////////////////
    if (dest instanceof File) {
      // files destinations
      // write statistics
      if (dest instanceof File) {
        dest = new File((File) dest, new StringBuffer(name).append(
            ".STX").toString());
      }
      // writing world file
      final PrintWriter p = new PrintWriter(new FileOutputStream(
          ((File) dest)));
      p.print(1);
      p.print(" ");
      p.print((int) Min[0]);
      p.print(" ");
      p.print((int) Max[0]);
      p.print(" ");
      p.print(hist.getMean()[0]);
      p.print(" ");
      p.print(hist.getStandardDeviation()[0]);
      p.close();
    } else {
      final ZipOutputStream outZ = (ZipOutputStream) dest;
      final ZipEntry e = new ZipEntry(name + ".STX");
      outZ.putNextEntry(e);


      // writing world file
      outZ.write("1".getBytes());
      outZ.write(" ".getBytes());
      outZ.write(new Integer((int) Min[0]).toString().getBytes());
      outZ.write(" ".getBytes());
      outZ.write(new Integer((int) Max[0]).toString().getBytes());
      outZ.write(" ".getBytes());
      outZ.write(new Double(hist.getMean()[0]).toString().getBytes());
      outZ.write(" ".getBytes());
      outZ.write(new Double(hist.getStandardDeviation()[0]).toString()
          .getBytes());
      ((ZipOutputStream) dest).closeEntry();
    }


    histogramImage.dispose();

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        // compute the histogram
        final RenderedOp hist = HistogramDescriptor.create(inputImage,
            null, Integer.valueOf(1), Integer.valueOf(1),
            new int[] { 256 }, new double[] { 0 },
            new double[] { 256 }, null);
        final Histogram h = (Histogram) hist.getProperty("histogram");


        // now compute the PDF and the CDF for the original image
        final byte[] cumulative = new byte[h.getNumBins(0)];


        // sum of bins (we might have excluded 0 hence we cannot really
        // optimise)
        float totalBinSum = 0;
        for (int i = 0; i < cumulative.length; i++) {
          totalBinSum += h.getBinSize(0, i);
        }


        // this is the scale factor for the histogram equalization
        // process
        final float scale = (float) (h.getHighValue(0) - 1 - h.getLowValue(0))/ totalBinSum;
        float sum = 0;
        for (int i = 1; i < cumulative.length; i++) {
          sum += h.getBinSize(0, i - 1);
          cumulative[i] = (byte) ((sum * scale + h.getLowValue(0)) + .5F);
        }


        final LookupTableJAI lookup = new LookupTableJAI(cumulative);
        final ParameterBlock pb = new ParameterBlock();
        pb.addSource(hist);

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        ParameterValueGroup param = processor.getOperation("Histogram").getParameters();
        param.parameter("Source").setValue(source);


        GridCoverage2D processed = (GridCoverage2D) processor.doOperation(param);


        Histogram histo = (Histogram) processed.getProperty("histogram");
        assertNotNull(histo);


        assertEquals(256, histo.getNumBins()[0]);
    }

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        param.parameter("Source").setValue(source);
        param.parameter("numBins").setValue(new int[]{10});
        
        GridCoverage2D processed = (GridCoverage2D) processor.doOperation(param);


        Histogram histo = (Histogram) processed.getProperty("histogram");
        assertNotNull(histo);


        assertEquals(10, histo.getNumBins()[0]);
    }

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        param.parameter("numBins").setValue(new int[]{10});
        param.parameter("lowValue").setValue(new double[]{100});
        param.parameter("highValue").setValue(new double[]{200});
        GridCoverage2D processed = (GridCoverage2D) processor.doOperation(param);


        Histogram histo = (Histogram) processed.getProperty("histogram");
        assertNotNull(histo);


        assertEquals(10, histo.getNumBins()[0]);
        assertEquals(100d, histo.getBinLowValue(0, 0), 0d);
        assertEquals(200d, histo.getBinLowValue(0, 10), 0d);
    }

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     * @param file
     * @return the deserialized histogram.
     */
    static Histogram getHistogram(final String file){
        Utilities.ensureNonNull("file", file);
        Histogram histogram = null;
        
        // Firstly: check if the histogram have been already
        // deserialized and it is available in cache
        if (ehcache != null && ehcache.isKeyInCache(file)){
            if (ehcache.isElementInMemory(file)){

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                        //setup dynamic threshold 
                        if (canonicalPath != null){
                            final String path = FilenameUtils.getFullPath(canonicalPath);
                            final String baseName = FilenameUtils.getBaseName(canonicalPath);
                            final String histogramPath = path + baseName + "." + "histogram";
                            final Histogram histogram = Utils.getHistogram(histogramPath);
                            if (histogram != null) {
                                final double[]p = histogram.getPTileThreshold(artifactsFilterPTileThreshold);
                                artifactThreshold = (int)p[0];
                            }
                        }
                    }
                    if (LOGGER.isLoggable(Level.FINE)){

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      fis = new FileImageInputStream(file);
      reader = spi.createReaderInstance();
      reader.setInput(fis);
      RenderedImage image = reader.read(0);
      RenderedOp histogramOp = HistogramDescriptor.create(image, null, Integer.valueOf(1), Integer.valueOf(1), new int[]{256}, null, null, null);
      Histogram histogram = (Histogram) histogramOp.getProperty("histogram");
      int[][] bins = histogram.getBins();
    
      assertEquals(bins[0][0],4261);
      assertEquals(bins[1][0],4261);
      assertEquals(bins[2][0],4832);
      assertEquals(bins[0][20],127); // This bin will disappear in the Histogram of the filtered image
      assertEquals(bins[1][20],127); // This bin will disappear in the Histogram of the filtered image
      assertEquals(bins[2][20],127); // This bin will disappear in the Histogram of the filtered image
      assertEquals(bins[0][180],571);
      assertEquals(bins[0][200],5041);
      assertEquals(bins[2][200],5041);
      assertEquals(bins[1][255],5612);
      
      assertEquals(bins[0][0]+bins[1][0]+bins[2][0]+bins[0][20]+bins[1][20]+bins[2][20]+bins[0][180]+bins[0][200]+bins[2][200]+bins[1][255], 100*100*3);
      
      // Image filtering
      ROI roi = new ROIShape(new Rectangle(14, 11, 75, 75));
      double [] backgroundValues = new double[]{0.0d, 0.0d, 0.0d};
      RenderedImage filtered = ArtifactsFilterDescriptor.create(image, roi, backgroundValues, 30, 3, null);
      histogramOp = HistogramDescriptor.create(filtered, null, Integer.valueOf(1), Integer.valueOf(1), new int[]{256}, null, null, null);
      histogram = (Histogram) histogramOp.getProperty("histogram");
      
      bins = histogram.getBins();
      
      assertEquals(bins[0][0],4261);
      assertEquals(bins[1][0],4261);
      assertEquals(bins[2][0],4845);
      assertEquals(bins[0][180],584);

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      imageChoice = new Integer(
          0);
    }


    final double[][] resolutionLevels = getResolutionLevels(coverageName);
    Histogram histogram = null;
    if (config.isEqualizeHistogram()) {
      histogram = getHistogram(
          coverageName,
          resolutionLevels[imageChoice.intValue()][0],
          resolutionLevels[imageChoice.intValue()][1]);

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      pb.add(1);
      pb.add(new int[]{bins}); 
      pb.add(new double[]{0});  
      pb.add(new double[]{256});
      PlanarImage dummy = JAI.create("histogram", pb);
      Histogram histogram = (Histogram) dummy.getProperty("histogram");
      dummy.setProperty("histogram", histogram.getBins());
      
    return ImageUtil.create(dummy);
  }

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