图像处理之噪声之美 - 随机噪声产生

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数学原理:

首先看两张图片,大小均为256 * 256个像素, 第一张是纯蓝色

图一:

第二张是加有随机噪声的蓝色

 图二:

产生随机噪声的算法简单的不能再简单了

假设RGB的R与G颜色分量均为零, 则 Blue = 255 * Math.Random() 随机数的取值范围在

[0, 1]之间, 程序的核心代码如下:

for(int row=0; row<256; row++) {

                            for(int col=0; col<256; col++) {

b = (int)(255.0d * Math.random());

                                     rgbData[index]= ((clamp(a) & 0xff) << 24) |

                                                                           ((clamp(r)& 0xff) << 16)  |

                                                                           ((clamp(g)& 0xff) << 8)   |

                                                                           ((clamp(b)& 0xff));

                                     index++;

                            }

}

 

上面显然不是我想要的结果,我想要的是下面两种:

 图三:


图四:


对的,只要我们对上面的算法稍加改进,就可以实现这样漂亮的噪声效果

实现第二张图效果的算法缺点在于,它每次都产生一个新的随机数,假设[0,1] = 255,接着第

二点随机可以能为[0, 2] = 0 第三个点可能随机值为[0, 3] = 125, 毫无规律可言,而我希望是

假设第一点随机[0, 1] = 255则间隔N个点以后再产生下个随机颜色值[0,N+1] =125, 在下一

个点则为[0, 2N +1] = 209…..于是问题产生了, 我们怎么计算[1, N]的之间的每个像素点的值

哇,这个问题不正是关于图像放缩的插值问题嘛,一个最简单的选择是双线性插值算法,

算法解释参考这里:http://blog.csdn.net/jia20003/article/details/6915185

有了算法选择,下面的问题就是我们怎么计算点值的问题,面临两个选择,一个值照搬双线

性插值中的计算方法,但是有点不自然,我们想要的是噪声,显然线性的计算结果不是最好

的最好的选择,cos(x)如何,在[0, PI]内是递减,在[PI,2PI]内是递增,而且值的范围在[-1, 1]

之间,而我们的随机数值要在[0, 1]之间于是综合上述考虑我们有cos(PI + (x-x0/x1-x0)* PI) + 1, 现

在计算出来的值是[0, 1]区间之内 根据插值公式最终有:

y= (y1-y0) * cos(PI + (x-x0/x1-x0) * PI) + 1 + y0

 

其中[x, y]代表要计算的点,周围四个采样点为:[x-N, y-N], [x+N,y-N], [x-N, y+N], [x+N, y+N ]

运用双线性插值原理即可计算出[1, N]个每个像素点的值。


关键代码实现及解释:

获取四个采样点,及其值,然后使用类似双线性算法计算出[x,y]的随机数值进而计算出像素值

的程序代码如下:

// bi-line interpolation algorithm here!!!    Double GetColor(int x, int y, int M, int colorType)    {       int x0 = x - (x % M);       int x1 = x0 + M;       int y0 = y - (y % M);       int y1 = y0 + M;         Double x0y0 = Noise(x0,y0, colorType);        Double x1y0 = Noise(x1,y0, colorType);        Double x0y1 = Noise(x0,y1, colorType);        Double x1y1 = Noise(x1,y1, colorType);         Double xx0 =Interpolate(x0, x0y0, x1, x1y0, x);        Double xx1 = Interpolate(x0,x0y1, x1, x1y1, x);         Double N =Interpolate(y0, xx0, y1, xx1, y);        return N;    }

根据两个点计算插入值的公式代码如下:

return (1.0 + Math.cos(Math.PI +  (Math.PI / (x1-x0)) * (x-x0))) / 2.0 * (xx1-xx0) + xx0;

对一张图像实现随机噪声值得出像素值计算的代码如下:

                for(int row=0; row<256; row++) {for(int col=0; col<256; col++) {// set random color value for each pixelr = (int)(255.0d * GetColor(row, col, intervalPixels, 1));g = (int)(255.0d * GetColor(row, col, intervalPixels, 2));b = (int)(255.0d * GetColor(row, col, intervalPixels, 4));rgbData[index] = ((clamp(a) & 0xff) << 24) |((clamp(r) & 0xff) << 16)  |((clamp(g) & 0xff) << 8)   |((clamp(b) & 0xff));index++;}}
完全源代码如下:

import java.awt.BorderLayout;import java.awt.Dimension;import java.awt.Graphics;import java.awt.Graphics2D;import java.awt.RenderingHints;import java.awt.image.BufferedImage;import java.util.Random;import javax.swing.JComponent;import javax.swing.JFrame;public class RandomNoiseImage extends JComponent {/** *  */private static final long serialVersionUID = -2236160343614397287L;private BufferedImage image = null;private double[] blue_random;private double[] red_random;private double[] green_random;private int intervalPixels = 40; // defaultpublic RandomNoiseImage() {super();this.setOpaque(false);}protected void paintComponent(Graphics g) {Graphics2D g2 = (Graphics2D)g;g2.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON);g2.drawImage(getImage(), 5, 5, image.getWidth(), image.getHeight(), null);}private BufferedImage getImage() {if(image == null) {image = new BufferedImage(256, 256, BufferedImage.TYPE_INT_ARGB);int[] rgbData = new int[256*256];generateNoiseImage(rgbData);setRGB(image, 0, 0, 256, 256, rgbData);}return image;}private void generateNoiseImage(int[] rgbData) {int index = 0;int a = 255;int r = 0;int g = 0;int b = 0;int sum = 256 * 256;blue_random = new double[sum];red_random = new double[sum];green_random = new double[sum];Random random = new Random();for(int i=0; i< sum; i++) {blue_random[i] = random.nextDouble();red_random[i] = random.nextDouble();green_random[i] = random.nextDouble();}for(int row=0; row<256; row++) {for(int col=0; col<256; col++) {// set random color value for each pixelr = (int)(255.0d * GetColor(row, col, intervalPixels, 1));g = (int)(255.0d * GetColor(row, col, intervalPixels, 2));b = (int)(255.0d * GetColor(row, col, intervalPixels, 4));rgbData[index] = ((clamp(a) & 0xff) << 24) |((clamp(r) & 0xff) << 16)  |((clamp(g) & 0xff) << 8)   |((clamp(b) & 0xff));index++;}}}private int clamp(int rgb) {if(rgb > 255)return 255;if(rgb < 0)return 0;return rgb;}// bi-line interpolation algorithm here!!!Double GetColor(int x, int y, int M, int colorType){int x0 = x - (x % M);int x1 = x0 + M;int y0 = y - (y % M);int y1 = y0 + M;    Double x0y0 = Noise(x0, y0, colorType);    Double x1y0 = Noise(x1, y0, colorType);    Double x0y1 = Noise(x0, y1, colorType);    Double x1y1 = Noise(x1, y1, colorType);    Double xx0 = Interpolate(x0, x0y0, x1, x1y0, x);    Double xx1 = Interpolate(x0, x0y1, x1, x1y1, x);    Double N = Interpolate(y0, xx0, y1, xx1, y);    return N;}// algorithm selection here !!!private Double Interpolate(double x0, double xx0, double x1, double xx1, double x) {return (1.0 + Math.cos(Math.PI +       (Math.PI / (x1-x0)) * (x-x0))) / 2.0 * (xx1-xx0) + xx0;}Double Noise(int x, int y, int colorType){if(colorType == 1) {if (x < 256 && y < 256)        return red_random[y * 256 + x];    else        return 0.0;} else if(colorType == 2) {if (x < 256 && y < 256)        return green_random[y * 256 + x];    else        return 0.0;} else {if (x < 256 && y < 256)        return blue_random[y * 256 + x];    else        return 0.0;}}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 );    }public static void main(String[] args) {JFrame frame = new JFrame("Noise Art Panel");frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);frame.getContentPane().setLayout(new BorderLayout());// Display the window.frame.getContentPane().add(new RandomNoiseImage(), BorderLayout.CENTER);frame.setPreferredSize(new Dimension(280,305));frame.pack();frame.setVisible(true);}}




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