Java对图像的处理，具有相当强的表现能力，下列程序可以将普通照片生成类似于手绘的素描。

import java.awt.color.ColorSpace;

import java.awt.image.BufferedImage;

import java.awt.image.ColorConvertOp;

import java.io.File;

import javax.imageio.ImageIO;

public class sketch {

public static void main(String[] args) throws Exception{

String file1 = "D:/1.jpg";//原文件

String file2 = "D:/2.jpg";//素描

File inputFile = new File(file1);

BufferedImage old = ImageIO.read(inputFile);

//去色

BufferedImage b1 = discolor(old);

//反相

b1 = invert(b1);

//高斯模糊

float[][] matric = gaussian2DKernel(3, 3f);

b1 = convolution(b1, matric);

//叠加

b1 = deceaseColorCompound(old, b1);

//黑白

ColorSpace cs1 = ColorSpace.getInstance(ColorSpace.CS_GRAY);

ColorConvertOp op1 = new ColorConvertOp(cs1, null);

BufferedImage b2 = new BufferedImage(old.getWidth(), old.getHeight(), BufferedImage.TYPE_INT_RGB);

op1.filter(b1, b2);

ImageIO.write(b2, "jpg", new File(file2));

System.out.println("生成素描");

}

//去色

public static BufferedImage discolor(final BufferedImage sourceImage) {

final int width = sourceImage.getWidth();

final int height = sourceImage.getHeight();

final BufferedImage retImage = new BufferedImage(width, height,

BufferedImage.TYPE_INT_ARGB);

for (int i = 0; i < width; i++) {

for (int j = 0; j < height; j++) {

final int color1 = sourceImage.getRGB(i, j);

final int a1 = (color1 >> 24) & 0xff;

final int r1 = (color1 >> 16) & 0xff;

final int g1 = (color1 >> 8) & 0xff;

final int b1 = color1 & 0xff;

double sumA = a1;

double sumR = 0;

double sumG = 0;

double sumB = 0;

sumR = sumG = sumB = r1 * 0.299 + g1 * 0.587 + b1 * 0.114;

final int result = (((int) sumA)<<24)

| (((int) sumR) << 16) | (((int) sumG) << 8) | ((int) sumB);

retImage.setRGB(i, j, result);

}

}

return retImage;

}

//反相

public static BufferedImage invert(final BufferedImage sourceImage) {

final int width = sourceImage.getWidth();

final int height = sourceImage.getHeight();

final BufferedImage retImage = new BufferedImage(width, height,

BufferedImage.TYPE_INT_ARGB);

for (int i = 0; i < width; i++) {

for (int j = 0; j < height; j++) {

final int color1 = sourceImage.getRGB(i, j);

final int a1 = (color1 >> 24) & 0xff;

final int r1 = (color1 >> 16) & 0xff;

final int g1 = (color1 >> 8) & 0xff;

final int b1 = color1 & 0xff;

int a = a1;

int r = 255 - r1;

int g = 255 - g1;

int b = 255 - b1;

int result = (a << 24) | (r << 16) | (g << 8) | b;

if(result > 255) result = 255;

retImage.setRGB(i, j, result);

}

}

return retImage;

}

//叠加：两张图片颜色减淡混合

// C =MIN( A +(A×B)/(256-B),255)

public static BufferedImage deceaseColorCompound(final BufferedImage sourceImage,

final BufferedImage targetImage) {

final int width = sourceImage.getWidth() > targetImage.getWidth() ? sourceImage

.getWidth() : targetImage.getWidth();

final int height = sourceImage.getHeight() > targetImage.getHeight() ? sourceImage

.getHeight() : targetImage.getHeight();

final BufferedImage retImage = new BufferedImage(width, height,

BufferedImage.TYPE_INT_ARGB);

for (int i = 0; i < width; i++) {

for (int j = 0; j < height; j++) {

if(i>=sourceImage.getWidth() || j>=sourceImage.getHeight()){

if(i>=targetImage.getWidth() || j>=targetImage.getHeight()){

retImage.setRGB(i, j, 0);

continue;

}

retImage.setRGB(i, j, targetImage.getRGB(i, j));

continue;

}

if(i>=targetImage.getWidth() || j>=targetImage.getHeight()){

retImage.setRGB(i, j, sourceImage.getRGB(i, j));

continue;

}

final int color1 = sourceImage.getRGB(i, j);

final int color2 = targetImage.getRGB(i, j);

final int a1 = (color1 >> 24) & 0xff;

final int r1 = (color1 >> 16) & 0xff;

final int g1 = (color1 >> 8) & 0xff;

final int b1 = color1 & 0xff;

final int a2 = (color2 >> 24) & 0xff;

final int r2 = (color2 >> 16) & 0xff;

final int g2 = (color2 >> 8) & 0xff;

final int b2 = color2 & 0xff;

final int a = deceaseColorChannel(a1, a2);

final int r = deceaseColorChannel(r1, r2);

final int g = deceaseColorChannel(g1, g2);

final int b = deceaseColorChannel(b1, b2);

final int result = (a << 24) | (r << 16) | (g << 8) | b;

retImage.setRGB(i, j, result);

}

}

return retImage;

}

// C =MIN( A +(A×B)/(256-B),255)

private static int deceaseColorChannel(final int source, final int target) {

final int result = source + source * target / (256 - target);

return result > 255 ? 255 : result;

}

//高斯模糊

public static BufferedImage convolution(final BufferedImage image,

final float kernel[][]) {

final int width = image.getWidth();

final int height = image.getHeight();

final int radius = kernel.length / 2;

final BufferedImage retImage = new BufferedImage(width, height,

BufferedImage.TYPE_INT_ARGB);

for (int i = 0; i < width; i++) {

for (int j = 0; j < height; j++) {

double sumA = 0;

double sumR = 0;

double sumG = 0;

double sumB = 0;

for (int x = i - radius; x <= i + radius; x++) {

for (int y = j - radius; y <= j + radius; y++) {

final int posX = x < 0 ? 0 : x >= width ? width - 1 : x;

final int posY = y < 0 ? 0 : y >= height ? height - 1

: y;

final int color = image.getRGB(posX, posY);

final int a = (color >> 24) & 0xff;

final int r = (color >> 16) & 0xff;

final int g = (color >> 8) & 0xff;

final int b = color & 0xff;

final int kelX=x - i + radius;

final int kelY=y - j + radius;

sumA += kernel[kelX][kelY] * a;

sumR += kernel[kelX][kelY] * r;

sumG += kernel[kelX][kelY] * g;

sumB += kernel[kelX][kelY] * b;

}

}

final int blurColor = (((int) sumA)<<24)

| (((int) sumR) << 16) | (((int) sumG) << 8) | ((int) sumB);

retImage.setRGB(i, j, blurColor);

}

}

return retImage;

}

//2D高斯卷积矩阵

// G(x,y)=[1/(2*PI*sigma^2)]*e^[-((x^2+y^2)/(2*sigma^2))]

// x,y->[-radius,radius)

public static float[][] gaussian2DKernel(final int radius, final float sigma) {

final int length = 2 * radius;

final float[][] matric = new float[length + 1][length + 1];

final float sigmaSquare2 = 2 * sigma * sigma;

float sum = 0;

for (int x = -radius; x <= radius; x++) {

for (int y = -radius; y <= radius; y++) {

matric[radius + x][radius + y] = (float) (Math.pow(Math.E, -(x

* x + y * y)

/ sigmaSquare2) / (Math.PI * sigmaSquare2));

sum += matric[radius + x][radius + y];

}

}

for (int x = 0; x < length; x++) {

for (int y = 0; y < length; y++) {

matric[x][y] /= sum;

}

}

return matric;

}

}

生成效果比较

生成前照片：

生成后素描：