java代码降低噪声 java减少运行时间( 七 )

//原文地址
java数字图像处理常用算法前些时候做毕业设计用java做的数字图像处理方面的东西这方面的资料ms比较少发点东西上来大家共享一下主要就是些算法有自己写的有人家的还有改人家的有的算法写的不好大家不要见笑
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
publicvoid getBMPImage(String source) throws Exception {clearNData();//清除数据保存区FileInputStream fs = null;try {fs = new FileInputStream(source);int bfLen = ;byte bf[] = new byte[bfLen];fs read(bf bfLen); // 读取字节BMP文件头int biLen = ;byte bi[] = new byte[biLen];fs read(bi biLen); // 读取字节BMP信息头
// 源图宽度nWidth = (((int) bi[ ]xff))| (((int) bi[ ]xff))| (((int) bi[ ]xff)) | (int) bi[ ]xff;
// 源图高度nHeight = (((int) bi[ ]xff))| (((int) bi[ ]xff))| (((int) bi[ ]xff)) | (int) bi[ ]xff;
// 位数nBitCount = (((int) bi[ ]xff)) | (int) bi[ ]xff;
// 源图大小int nSizeImage = (((int) bi[ ]xff))| (((int) bi[ ]xff))| (((int) bi[ ]xff)) | (int) bi[ ]xff;
// 对位BMP进行解析if (nBitCount == ){int nPad = (nSizeImage / nHeight) nWidth * ;nData = https://www.04ip.com/post/new int[nHeight * nWidth];nB=new int[nHeight * nWidth];nR=new int[nHeight * nWidth];nG=new int[nHeight * nWidth];byte bRGB[] = new byte[(nWidth + nPad) * * nHeight];fs read(bRGB (nWidth + nPad) * * nHeight);int nIndex = ;for (int j = ; jnHeight; j++){for (int i = ; inWidth; i++) {nData[nWidth * (nHeight j ) + i] = (xff)| (((int) bRGB[nIndex + ]xff))| (((int) bRGB[nIndex + ]xff))| (int) bRGB[nIndex]xff;nB[nWidth * (nHeight j ) + i]=(int) bRGB[nIndex] xff;nG[nWidth * (nHeight j ) + i]=(int) bRGB[nIndex+ ] xff;nR[nWidth * (nHeight j ) + i]=(int) bRGB[nIndex+ ] xff;nIndex += ;}nIndex += nPad;} //Toolkit kit = Toolkit getDefaultToolkit(); //image = kit createImage(new MemoryImageSource(nWidth nHeight//nData nWidth));
/*//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= ;jnHeight;j++){for(int i= ;inWidth;i++){out print(( * +nData[nWidth * (nHeight j ) + i])+ _+nR[nWidth * (nHeight j ) + i]+ _+nG[nWidth * (nHeight j ) + i]+ _+nB[nWidth * (nHeight j ) + i]+ );}out println( );}out close();*/}}catch (Exception e) {e printStackTrace();throw new Exception(e);}finally {if (fs != null) {fs close();}}//return image;}
二由r g b 获取灰度数组
publicint[] getBrightnessData(int rData[] int gData[] int bData[]){int brightnessData[]=new int[rData length];if(rData length!=gData length || rData length!=bData length|| bData length!=gData length){return brightnessData;}else {for(int i= ;ibData length;i++){double temp= *rData[i]+ *gData[i]+ *bData[i];brightnessData[i]=(int)(temp)+((temp (int)(temp)) ? : );}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];int SumGray[]=new int[ ];int ImageDestination[]=new int[length];for(int i = ; i length ;i++){gray=PixelsGray[i];FrequenceGray[gray]++;}//灰度均衡化SumGray[ ]=FrequenceGray[ ];for(int i= ;i ;i++){SumGray[i]=SumGray[i ]+FrequenceGray[i];}for(int i= ;i ;i++) {SumGray[i]=(int)(SumGray[i]* /length);}for(int i= ;iheight;i++){for(int j= ;jwidth;j++){int k=i*width+j;ImageDestination[k]= xFF | ((SumGray[PixelsGray[k]]) | (SumGray[PixelsGray[k]] ) | SumGray[PixelsGray[k]]);}}return ImageDestination;}
四 laplace 阶滤波增强边缘图像锐化
public int[] laplace DFileter(int []data int width int height){int filterData[]=new int[data length];int min= ;int max= ;for(int i= ;iheight;i++){for(int j= ;jwidth;j++){if(i== || i==height || j== || j==width )filterData[i*width+j]=data[i*width+j];elsefilterData[i*width+j]= *data[i*width+j] data[i*width+j ] data[i*width+j+ ]data[(i )*width+j] data[(i )*width+j ] data[(i )*width+j+ ]data[(i+ )*width+j] data[(i+ )*width+j ] data[(i+ )*width+j+ ];if(filterData[i*width+j]min)min=filterData[i*width+j];if(filterData[i*width+j]max)max=filterData[i*width+j];}}//System out println( max: +max);//System out println( min: +min);for(int i= ;iwidth*height;i++){filterData[i]=(filterData[i] min)* /(max min);}return filterData;}