JAVA图像处理实例

/* //调试数据的读取
FileWriter fw = new FileWriter("C://Documents and Settings//Administrator//My Documents//nDataRaw.txt");//创建新文件
PrintWriter out = new PrintWriter(fw); for(int j=0;j<nHeight;j++){
int SumGray[]=new int[256];
int ImageDestination[]=new int[length];
for(int i = 0; i <length ;i++)
{
gray=PixelsGray[i];
FrequenceGray[gray]++;
}
//
灰度均衡化
SumGray[0]=FrequenceGray[0];
byte bRGB[] = new byte[(nWidth + nPad) *
3 * nHeight];
fs.read(bRGB, 0, (nWidth + nPad) * 3 *
nHeight);
int nIndex = 0;
for (int j = 0; j < nHeight; j++){
for (int i = 0; i < nWidth; i++)
idth+j]-data[(i+1)*width+j-1]-data[(i+1)*width+j+1];
if(filterData[i*width+j]<min)
min=filterData[i*width+j];
if(filterData[i*width+j]>max)
max=filterData[i*width+j];
|| bData.length!=gData.length){ return brightnessData; } else { for(int i=0;i<bData.length;i++){
double temp=0.3*rData[i]+0.59*gData[i]+0.11*bData[i]; brightnessData[i]=(int)(temp)+((temp-(int)(temp))>0.5?1:
二 由 r g b 获取灰度数组
public int[] getBrightnessData(int rData[],int gData[],int bData[]){
int brightnessData[]=new int[rData.length]; if(rData.length!=gData.length || rData.length!=bData.length
nIndex += 3;
}
nIndex += nPad;}//源自Toolkit kit =
Toolkit.getDefaultToolkit();
//
image = kit.createImage(new
MemoryImageSource(nWidth, nHeight,
//
nData, 0, nWidth));
nB[nWidth * (nHeight - j
- 1) + i]=(int) bRGB[nIndex]& 0xff;
nG[nWidth * (nHeight - j
- 1) + i]=(int) bRGB[nIndex+1]& 0xff;
nR[nWidth * (nHeight - j
- 1) + i]=(int) bRGB[nIndex+2]& 0xff;
} } return ImageDestination;
}
四 laplace2 阶滤波，增强边缘,图像锐化
public int[] laplace2DFileter(int []data,int width,int height){
int filterData[]=new int[data.length];
0); } return brightnessData;
}
}
三 直方图均衡化
public int [] equilibrateGray(int[] PixelsGray,int width,int
height)
{
int gray;
int length=PixelsGray.length;
int FrequenceGray[]=new int[length];
* (nHeight - j - 1) + i])+"_" i]+"_" i]+"_" i]+" ");
for(int i=0;i<nWidth;i++){ out.print((65536*256+nData[nWidth +nR[nWidth * (nHeight - j - 1) + +nG[nWidth * (nHeight - j - 1) + +nB[nWidth * (nHeight - j - 1) +
| (((int) bi[10] & 0xff) << 16) | (((int) bi[9] & 0xff) << 8) |
bi[14] & 0xff;
// 位数 nBitCount = (((int) bi[15] & 0xff) << 8) | (int)
(int) bi[20] & 0xff;
{
nData[nWidth * (nHeight
- j - 1) + i] = (255 & 0xff) << 24
|
(((int) bRGB[nIndex + 2] & 0xff) << 16)
|
(((int) bRGB[nIndex + 1] & 0xff) << 8)
| (int)
bRGB[nIndex] & 0xff;
一 读取 bmp 图片数据 // 获取待检测图像 ，数据保存在数组 nData[]，nB[] ，nG[] ，nR[]中
public void getBMPImage(String source) throws Exception {
clearNData(); //清除数据保存区
FileInputStream fs = null;
} return filterData; }
五 laplace2 阶增强滤波，增强边缘，增强系数 delt
public int[] laplaceHigh2DFileter(int []data,int width,int height,double delt){
int filterData[]=new int[data.length]; int min=10000; int max=-10000; for(int i=0;i<height;i++){
try {
fs = new FileInputStream(source); int bfLen = 14; byte bf[] = new byte[bfLen]; fs.read(bf, 0, bfLen); // 读取 14 字节 BMP 文件头 int biLen = 40; byte bi[] = new byte[biLen]; fs.read(bi, 0, biLen); // 读取 40 字节 BMP 信息头
for(int i=1;i<256;i++){
SumGray[i]=SumGray[i-1]+FrequenceGray[i];
} for(int i=0;i<256;i++) {
SumGray[i]=(int)(SumGray[i]*255/length);
} for(int i=0;i<height;i++) {
for(int j=0;j<width;j++) {
int k=i*width+j; ImageDestination[k]=0xFF000000 | ((SumGray[PixelsGray[k]]<<
16 ) | (SumGray[PixelsGray[k]]<< 8 ) | SumGray[PixelsGray[k]]);
(int) bi[4] & 0xff; (int) bi[8] & 0xff;
// 源图宽度 nWidth = (((int) bi[7] & 0xff) << 24)
| (((int) bi[6] & 0xff) << 16) | (((int) bi[5] & 0xff) << 8) |
// 源图高度 nHeight = (((int) bi[11] & 0xff) << 24)
}
}
//
System.out.println("max: "+max);
//
System.out.println("min: "+min);