映像分析之長條圖分析

映像分析之強度長條圖分析

長條圖介紹

強度長條圖圖形化顯示不同的像素值在不同的強度值上的出現頻率，對於灰階映像來說強度

範圍為[0~255]之間，對於RGB的彩色映像可以獨立顯示三種顏色的強度長條圖。強度直方

圖是用來尋找灰階映像二值化閾值常用而且是有效手段之一，如果一幅灰階映像的長條圖

顯示為兩個波峰，則二值化閾值應該是這兩個波峰之間的某個灰階值。同時強度長條圖是調

整映像對比的重要依據

 

長條圖實現方法：

對一幅灰階映像從上到下，從左至右掃描每個像素值，在每個灰階值上計算像素數目，以這

些資料為基礎完成映像長條圖的繪製。

運行效果如下：

程式實現：

1.      首先對一幅RGB映像完成灰階轉換，轉碼如下：

2.      初始化長條圖資料數組int[256] 因為灰階值的範圍為0～255

3.      掃描灰階映像，完成強度資料計算。

4.      使用Java 2D繪製長條圖

 

長條圖實現原始碼：

package com.gloomyfish.image.analysis;import java.awt.Color;import java.awt.Graphics2D;import java.awt.image.BufferedImage;public class HistogramAnalysisAlg {private BufferedImage srcImage;private BufferedImage histogramImage;private int size = 280;public HistogramAnalysisAlg(BufferedImage srcImage){histogramImage = new BufferedImage(size,size, BufferedImage.TYPE_4BYTE_ABGR);this.srcImage = srcImage;}public BufferedImage getHistogram() {        int[] inPixels = new int[srcImage.getWidth()*srcImage.getHeight()];        int[] intensity = new int[256];        for(int i=0; i<intensity.length; i++) {        intensity[i] = 0;        }        getRGB( srcImage, 0, 0, srcImage.getWidth(), srcImage.getHeight(), inPixels );        int index = 0;        for(int row=0; row<srcImage.getHeight(); row++) {        int ta = 0, tr = 0, tg = 0, tb = 0;        for(int col=0; col<srcImage.getWidth(); col++) {        index = row * srcImage.getWidth() + col;        ta = (inPixels[index] >> 24) & 0xff;                tr = (inPixels[index] >> 16) & 0xff;                tg = (inPixels[index] >> 8) & 0xff;                tb = inPixels[index] & 0xff;                int gray = (int)(0.299 * (double)tr + 0.587 * (double)tg + 0.114 * (double)tb);                intensity[gray]++;        }        }                // draw XY Axis lines        Graphics2D g2d = histogramImage.createGraphics();        g2d.setPaint(Color.BLACK);        g2d.fillRect(0, 0, size, size);        g2d.setPaint(Color.WHITE);        g2d.drawLine(5, 250, 265, 250);        g2d.drawLine(5, 250, 5, 5);                // scale to 200        g2d.setPaint(Color.GREEN);        int max = findMaxValue(intensity);        float rate = 200.0f/((float)max);        int offset = 2;        for(int i=0; i<intensity.length; i++) {        int frequency = (int)(intensity[i] * rate);        g2d.drawLine(5 + offset + i, 250, 5 + offset + i, 250-frequency);        }                // X Axis Gray intensity        g2d.setPaint(Color.RED);        g2d.drawString("Gray Intensity", 100, 270);return histogramImage;}private int findMaxValue(int[] intensity) {int max = -1;for(int i=0; i<intensity.length; i++) {if(max < intensity[i]) {max = intensity[i];}}return max;}/** * A convenience method for getting ARGB pixels from an image. This tries to avoid the performance * penalty of BufferedImage.getRGB unmanaging the image. */public int[] getRGB( BufferedImage image, int x, int y, int width, int height, int[] pixels ) {int type = image.getType();if ( type == BufferedImage.TYPE_INT_ARGB || type == BufferedImage.TYPE_INT_RGB )return (int [])image.getRaster().getDataElements( x, y, width, height, pixels );return image.getRGB( x, y, width, height, pixels, 0, width );    }/** * A convenience method for setting ARGB pixels in an image. This tries to avoid the performance * penalty of BufferedImage.setRGB unmanaging the image. */public void setRGB( BufferedImage image, int x, int y, int width, int height, int[] pixels ) {int type = image.getType();if ( type == BufferedImage.TYPE_INT_ARGB || type == BufferedImage.TYPE_INT_RGB )image.getRaster().setDataElements( x, y, width, height, pixels );elseimage.setRGB( x, y, width, height, pixels, 0, width );    }}

測試代碼如下：

package com.gloomyfish.image.analysis;import java.awt.Dimension;import java.awt.Graphics;import java.awt.Graphics2D;import java.awt.MediaTracker;import java.awt.image.BufferedImage;import java.io.File;import java.io.IOException;import javax.imageio.ImageIO;import javax.swing.JComponent;import javax.swing.JFileChooser;import javax.swing.JFrame;public class ImageAnalysisUI  extends JComponent {/** *  */private static final long serialVersionUID = 1518574788794973574L;private BufferedImage rawImg;private BufferedImage modImg;private MediaTracker tracker;private Dimension mySize;public ImageAnalysisUI(File f) {try {rawImg = ImageIO.read(f);HistogramAnalysisAlg filter = new HistogramAnalysisAlg(rawImg);modImg = filter.getHistogram();} catch (IOException e1) {e1.printStackTrace();}tracker = new MediaTracker(this);tracker.addImage(rawImg, 1);// blocked 10 seconds to load the image datatry {if (!tracker.waitForID(1, 10000)) {System.out.println("Load error.");System.exit(1);}// end if} catch (InterruptedException e) {e.printStackTrace();System.exit(1);}// end catchmySize = new Dimension(2*rawImg.getWidth() + 20, rawImg.getHeight()*2);JFrame imageFrame = new JFrame("Gloomyfish - Image Analysis");imageFrame.getContentPane().add(this);imageFrame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);imageFrame.pack();imageFrame.setVisible(true);}public void paint(Graphics g) {Graphics2D g2 = (Graphics2D) g;g2.drawImage(rawImg, 0, 0, rawImg.getWidth(), rawImg.getHeight(), null);g2.drawImage(modImg, rawImg.getWidth()+10, 0, modImg.getWidth(), modImg.getHeight(), null);g2.drawString("source image", 10, rawImg.getHeight() +10);g2.drawString("connected component labeled area", 10 + modImg.getWidth(), rawImg.getHeight() +10);}public Dimension getPreferredSize() {return mySize;}public Dimension getMinimumSize() {return mySize;}public Dimension getMaximumSize() {return mySize;}public static void main(String[] args) {JFileChooser chooser = new JFileChooser();chooser.showOpenDialog(null);File f = chooser.getSelectedFile();new ImageAnalysisUI(f);}}

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