[Android] 通过Menu实现图片怀旧、浮雕、模糊、光照和素描效果

由于随手拍项目想做成类似于美图秀秀那种底部有一排Menu实现不同效果的功能,这里先简单介绍如何通过Menu实现打开相册中的图片、怀旧效果、浮雕效果、光照效果和素描效果.后面可能会讲述如何通过PopupWindow实现自定义的Menu效果.
希望文章对大家有所帮助,如果有错误或不足之处请海涵~

一. Menu效果展示

Android手机上有个Menu按键,点击他会弹出一个菜单,通常在屏幕底部或右上角,在选项菜单OptionsMenu中最多显示2排每排3个菜单项,可以包含自定义的图片和文字.如果Menu菜单项多于6项时,第6项(Expanded Menus,扩展菜单)会变成More,点击它会显示后面所隐藏的所有选项.
下面讲述如何在Android 4.0项目中实现简单的Menu功能.添加如下代码：

@Override
public boolean onCreateOptionsMenu(Menu menu) { //创建Menu//自定义menu 添加图标(使用自带图标)menu.add(Menu.NONE, Menu.FIRST + 1 , 1, "打开").setIcon(android.R.drawable.ic_menu_slideshow);menu.add(Menu.NONE, Menu.FIRST + 2 , 2, "怀旧").setIcon(android.R.drawable.ic_menu_edit);menu.add(Menu.NONE, Menu.FIRST + 3 , 3, "浮雕").setIcon(android.R.drawable.ic_menu_gallery);menu.add(Menu.NONE, Menu.FIRST + 4 , 4, "模糊").setIcon(android.R.drawable.ic_menu_crop);menu.add(Menu.NONE, Menu.FIRST + 5 , 5, "光照").setIcon(android.R.drawable.ic_menu_camera);menu.add(Menu.NONE, Menu.FIRST + 6  , 6, "锐化").setIcon(android.R.drawable.ic_menu_view);return true;
}

由于Android 4.0系统缺省UI风格有所变化,所以需要设置Activity的theme为Theme.Light.同时也可以在res/menu/main.xml设置菜单项.参考"恺风"博主关于Menu的介绍,非常不错.http://blog.csdn.net/flowingflying/article/details/11967301

<activityandroid:name="com.example.menushowimage.MainActivity"android:label="@string/app_name" android:theme="@android:style/Theme.Light" >

下图是设置前面的显示Menu不同效果,同时我调用的图标都是Android自带的图片,用户也可以自定义.(android默认图标列表)

同时设置XML格式显示图片:

<RelativeLayout xmlns:android="http://schemas.android.com/apk/res/android"xmlns:tools="http://schemas.android.com/tools"android:id="@+id/container"android:layout_width="match_parent"android:layout_height="match_parent"tools:context="com.example.touchimagetest.MainActivity"tools:ignore="MergeRootFrame" ><!-- 顶部添加文字 --><RelativeLayoutandroid:id="@+id/Layout_top"android:orientation="horizontal" android:layout_width="fill_parent"android:layout_height="25dp"android:layout_alignParentTop="true"android:gravity="center"><TextView  android:id="@+id/textView1"  android:layout_width="wrap_content"  android:layout_height="wrap_content"  android:textSize="20sp"  android:text="请点击menu处理图片" />  </RelativeLayout><!-- 底部显示图片 --><RelativeLayoutandroid:id="@+id/Layout_bottom" android:orientation="horizontal"android:layout_below="@id/Layout_top" android:layout_width="fill_parent" android:layout_height="wrap_content"android:background="#EFDFDF"android:gravity="center"><ImageViewandroid:id="@+id/imageView1"android:layout_width="fill_parent"android:layout_height="fill_parent"android:layout_gravity="center_horizontal" /></RelativeLayout>
</RelativeLayout>

二. Menu实现打开图片

然后通过onOptionsItemSelected(MenuItem item)实现选择图片,通过调用自定义函数实现各种功能.

@Override
public boolean onOptionsItemSelected(MenuItem item) { //选择Menu//选择id 对应Menu.add的参数Menu.FIRST+iint id = item.getItemId();switch(id) {case Menu.FIRST+1: Toast.makeText(this, "打开图片", Toast.LENGTH_SHORT).show();OpenImage();break;case Menu.FIRST+2: Toast.makeText(this, "图片怀旧效果", Toast.LENGTH_SHORT).show();OldRemeberImage();break;case Menu.FIRST+3: Toast.makeText(this, "图片浮雕效果", Toast.LENGTH_SHORT).show();ReliefImage();break;case Menu.FIRST+4: Toast.makeText(this, "图片模糊效果", Toast.LENGTH_SHORT).show();FuzzyImage();break;case Menu.FIRST+5: Toast.makeText(this, "图片光照效果", Toast.LENGTH_SHORT).show();SunshineImage();break;case Menu.FIRST+6: Toast.makeText(this, "图片锐化效果", Toast.LENGTH_SHORT).show();SharpenImage();break;}return super.onOptionsItemSelected(item);
}

其中打开图片函数实现方法如下,而上面的很多自定义函数都将在第三部分介绍,你此处可以注释掉只验证"打开图片".首先添加自定义变量和获取ImageView布局.

//自定义变量
private ImageView imageShow;           //显示图片  
private Bitmap bmp;                    //原始图片  
private final int IMAGE_OPEN = 0;      //打开图片 
@Override
protected void onCreate(Bundle savedInstanceState) {super.onCreate(savedInstanceState);setContentView(R.layout.activity_main);imageShow = (ImageView) findViewById(R.id.imageView1); if (savedInstanceState == null) {getFragmentManager().beginTransaction().add(R.id.container, new PlaceholderFragment()).commit();}
}

然后通过自定义函数OpenImage打开函数,与前面文章介绍的方法一样.

//自定义函数 打开图片
public void OpenImage()
{Intent intent = new Intent(Intent.ACTION_PICK,   android.provider.MediaStore.Images.Media.EXTERNAL_CONTENT_URI);  startActivityForResult(intent, IMAGE_OPEN);
}
//显示打开图片
protected void onActivityResult(int requestCode, int resultCode, Intent data) {   super.onActivityResult(requestCode, resultCode, data);    if(resultCode==RESULT_OK && requestCode==IMAGE_OPEN) {    Uri imageFileUri = data.getData();  DisplayMetrics dm = new DisplayMetrics();  getWindowManager().getDefaultDisplay().getMetrics(dm);    int width = dm.widthPixels;    //手机屏幕水平分辨率     int height = dm.heightPixels;  //手机屏幕垂直分辨率  try {    //载入图片尺寸大小没载入图片本身 true  BitmapFactory.Options bmpFactoryOptions = new BitmapFactory.Options();    bmpFactoryOptions.inJustDecodeBounds = true;    bmp = BitmapFactory.decodeStream(getContentResolver().openInputStream(imageFileUri), null, bmpFactoryOptions);    int heightRatio = (int)Math.ceil(bmpFactoryOptions.outHeight/(float)height);    int widthRatio = (int)Math.ceil(bmpFactoryOptions.outWidth/(float)width);      //inSampleSize表示图片占原图比例 1表示原图  if(heightRatio>1&&widthRatio>1) {    if(heightRatio>widthRatio) {    bmpFactoryOptions.inSampleSize = heightRatio;    }    else {    bmpFactoryOptions.inSampleSize = widthRatio;    }    }                     //图像真正解码 false  bmpFactoryOptions.inJustDecodeBounds = false;                   bmp = BitmapFactory.decodeStream(getContentResolver().openInputStream(imageFileUri), null, bmpFactoryOptions);      imageShow.setImageBitmap(bmp);  }  catch(FileNotFoundException e) {   e.printStackTrace();    }   }  //end if  
}

下面讲讲使用Options Menu的函数：
onCreateOptionsMenu(Menu menu)创建options menu,这个函数只会在menu第一次显示时调用.
onOptionsItemSelected(MenuItem item)处理选中的菜单项.
在通过menu.add函数实现添加菜单项,如menu.add(Menu.NONE,Menu.FIRST+1,1,"打开"),第一个参数表示组别;第二个参数menu标志编号与onOptionsItemSelected函数中值对应;第三个参数是在菜单中出现的顺序,顺序由小到大,由左至右;第四个参数是显示的文字,同时setIcon可以设置图标.

三. 图像各种效果实现

最后讲讲各个效果实现过程,通过不同自定义函数实现.其中各个效果主要参照《Android图像处理总结》那篇文章和eoeAndroid社区亚瑟的文章.
书籍下载地址：
1.图片怀旧效果

//图片怀旧处理
private void OldRemeberImage()
{/** 怀旧处理算法即设置新的RGB* R=0.393r+0.769g+0.189b* G=0.349r+0.686g+0.168b* B=0.272r+0.534g+0.131b*/int width = bmp.getWidth();int height = bmp.getHeight();Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);int pixColor = 0;int pixR = 0;int pixG = 0;int pixB = 0;int newR = 0;int newG = 0;int newB = 0;int[] pixels = new int[width * height];bmp.getPixels(pixels, 0, width, 0, 0, width, height);for (int i = 0; i < height; i++){for (int k = 0; k < width; k++){pixColor = pixels[width * i + k];pixR = Color.red(pixColor);pixG = Color.green(pixColor);pixB = Color.blue(pixColor);newR = (int) (0.393 * pixR + 0.769 * pixG + 0.189 * pixB);newG = (int) (0.349 * pixR + 0.686 * pixG + 0.168 * pixB);newB = (int) (0.272 * pixR + 0.534 * pixG + 0.131 * pixB);int newColor = Color.argb(255, newR > 255 ? 255 : newR, newG > 255 ? 255 : newG, newB > 255 ? 255 : newB);pixels[width * i + k] = newColor;}}bitmap.setPixels(pixels, 0, width, 0, 0, width, height);imageShow.setImageBitmap(bitmap);
}

显示效果如下图所示：

2.图片浮雕效果

//图片浮雕处理
//底片效果也非常简单:将当前像素点的RGB值分别与255之差后的值作为当前点的RGB
//灰度图像:通常使用的方法是gray=0.3*pixR+0.59*pixG+0.11*pixB
private void ReliefImage()
{/** 算法原理：(前一个像素点RGB-当前像素点RGB+127)作为当前像素点RGB值* 在ABC中计算B点浮雕效果(RGB值在0~255)* B.r = C.r - B.r + 127* B.g = C.g - B.g + 127* B.b = C.b - B.b + 127*/int width = bmp.getWidth();int height = bmp.getHeight();Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);int pixColor = 0;int pixR = 0;int pixG = 0;int pixB = 0;int newR = 0;int newG = 0;int newB = 0;int[] pixels = new int[width * height];bmp.getPixels(pixels, 0, width, 0, 0, width, height);for (int i = 1; i < height-1; i++){for (int k = 1; k < width-1; k++){//获取前一个像素颜色pixColor = pixels[width * i + k];   pixR = Color.red(pixColor);pixG = Color.green(pixColor);pixB = Color.blue(pixColor);//获取当前像素pixColor = pixels[(width * i + k) + 1];newR = Color.red(pixColor) - pixR +127;newG = Color.green(pixColor) - pixG +127;newB = Color.blue(pixColor) - pixB +127;newR = Math.min(255, Math.max(0, newR));newG = Math.min(255, Math.max(0, newG));newB = Math.min(255, Math.max(0, newB));pixels[width * i + k] = Color.argb(255, newR, newG, newB);}}bitmap.setPixels(pixels, 0, width, 0, 0, width, height);imageShow.setImageBitmap(bitmap);
}

显示效果如下图所示：

3.图像模糊效果

//图像模糊处理
private void FuzzyImage()
{/** 算法原理：* 简单算法将像素周围八个点包括自身共九个点RGB值分别相加后平均,当前像素点的RGB值* 复杂算法采用高斯模糊* 高斯矩阵 int[] gauss = new int[] { 1, 2, 1, 2, 4, 2, 1, 2, 1 };* 将九个点的RGB值分别与高斯矩阵中的对应项相乘的和,再除以一个相应的值作为当前像素点的RGB*/int[] gauss = new int[] { 1, 2, 1, 2, 4, 2, 1, 2, 1 };  // 高斯矩阵int delta = 16; // 除以值 值越小图片会越亮,越大则越暗int width = bmp.getWidth();int height = bmp.getHeight();Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);int pixColor = 0;int pixR = 0; int pixG = 0; int pixB = 0; int newR, newG, newB;int pos = 0;    //位置int[] pixels = new int[width * height]; bmp.getPixels(pixels, 0, width, 0, 0, width, height); //循环赋值for (int i = 1; i < height-1; i++){for (int k = 1; k < width-1; k++){pos = 0;newR = 0; newG = 0; newB = 0; for (int m = -1; m <= 1; m++)  //宽不变{ for (int n = -1; n <= 1; n++) //高先变{ pixColor = pixels[(i + m) * width + k + n]; pixR = Color.red(pixColor); pixG = Color.green(pixColor); pixB = Color.blue(pixColor); //3*3像素相加newR = newR + (int) (pixR * gauss[pos]); newG = newG + (int) (pixG * gauss[pos]); newB = newB + (int) (pixB * gauss[pos]); pos++; } } 			newR /= delta; newG /= delta; newB /= delta; newR = Math.min(255, Math.max(0, newR)); newG = Math.min(255, Math.max(0, newG)); newB = Math.min(255, Math.max(0, newB));      pixels[i * width + k] = Color.argb(255, newR, newG, newB);  }}bitmap.setPixels(pixels, 0, width, 0, 0, width, height);imageShow.setImageBitmap(bitmap);
}

该图显示效果不是很理想,对高斯模糊理解还不够,建议大家看我收藏合集里面讲述模糊的超链接.

4.图像光照效果

//图片光照效果
private void SunshineImage()
{/** 算法原理：(前一个像素点RGB-当前像素点RGB+127)作为当前像素点RGB值* 在ABC中计算B点浮雕效果(RGB值在0~255)* B.r = C.r - B.r + 127* B.g = C.g - B.g + 127* B.b = C.b - B.b + 127* 光照中心取长宽较小值为半径,也可以自定义从左上角射过来*/		int width = bmp.getWidth();int height = bmp.getHeight();Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);int pixColor = 0;int pixR = 0;int pixG = 0;int pixB = 0;int newR = 0;int newG = 0;int newB = 0;//围绕圆形光照int centerX = width / 2;int centerY = height / 2;int radius = Math.min(centerX, centerY);float strength = 150F;  //光照强度100-150int[] pixels = new int[width * height];bmp.getPixels(pixels, 0, width, 0, 0, width, height);for (int i = 1; i < height-1; i++){for (int k = 1; k < width-1; k++){//获取前一个像素颜色pixColor = pixels[width * i + k];   pixR = Color.red(pixColor);pixG = Color.green(pixColor);pixB = Color.blue(pixColor);newR = pixR;newG = pixG;newB = pixB;//计算当前点到光照中心的距离,平面坐标系中两点之间的距离int distance = (int) (Math.pow((centerY-i), 2) + Math.pow((centerX-k), 2));if(distance < radius*radius){//按照距离大小计算增强的光照值int result = (int)(strength*( 1.0-Math.sqrt(distance) / radius ));newR = pixR + result;newG = newG + result;newB = pixB + result;}newR = Math.min(255, Math.max(0, newR));newG = Math.min(255, Math.max(0, newG));newB = Math.min(255, Math.max(0, newB));pixels[width * i + k] = Color.argb(255, newR, newG, newB);}}bitmap.setPixels(pixels, 0, width, 0, 0, width, height);imageShow.setImageBitmap(bitmap);
}

显示效果如下图所示

5.图片锐化效果
本打算采用拉普拉斯算子或Sobel算子对图像进行锐化,在使用C++对24位bmp图像处理时能非常好的显示图像的轮廓,但是Android总是效果不是很好啊,而且有虚线!网上一些锐化效果完全没有实现显示图像轮廓,与原图区别不大,感觉是错误的方法.研究ing

//图像锐化处理 拉普拉斯算子处理
private void SharpenImage()
{/** 锐化基本思想是加强图像中景物的边缘和轮廓,使图像变得清晰* 而图像平滑是使图像中边界和轮廓变得模糊* * 拉普拉斯算子图像锐化* 获取周围9个点的矩阵乘以模板9个的矩阵 卷积*///拉普拉斯算子模板 { 0, -1, 0, -1, -5, -1, 0, -1, 0 } { -1, -1, -1, -1, 9, -1, -1, -1, -1 }int[] laplacian = new int[] {  -1, -1, -1, -1, 9, -1, -1, -1, -1 }; int width = bmp.getWidth();  int height = bmp.getHeight();  Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);  int pixR = 0;  int pixG = 0;  int pixB = 0;  int pixColor = 0;  int newR = 0;  int newG = 0;  int newB = 0;  int idx = 0;  float alpha = 0.3F;  //图片透明度int[] pixels = new int[width * height];  bmp.getPixels(pixels, 0, width, 0, 0, width, height);  //图像处理for (int i = 1; i < height - 1; i++)  {  for (int k = 1; k < width - 1; k++)  {  idx = 0;newR = 0;  newG = 0;  newB = 0;  for (int n = -1; n <= 1; n++)   //取出图像3*3领域像素 {  for (int m = -1; m <= 1; m++)  //n行数不变 m列变换{  pixColor = pixels[(i + n) * width + k + m];  //当前点(i,k)pixR = Color.red(pixColor);  pixG = Color.green(pixColor);  pixB = Color.blue(pixColor);  //图像像素与对应摸板相乘   newR = newR + (int) (pixR * laplacian[idx] * alpha);  newG = newG + (int) (pixG * laplacian[idx] * alpha);  newB = newB + (int) (pixB * laplacian[idx] * alpha);  idx++; }  }newR = Math.min(255, Math.max(0, newR));  newG = Math.min(255, Math.max(0, newG));  newB = Math.min(255, Math.max(0, newB));  //赋值  pixels[i * width + k] = Color.argb(255, newR, newG, newB);   }}bitmap.setPixels(pixels, 0, width, 0, 0, width, height);  imageShow.setImageBitmap(bitmap);
}

作图是其显示效果,而右图是我以前《数字图像处理》课用C++写的不同模版的锐化效果.

下面再介绍些效果,下面这个效果是参考亚瑟BOY的冰冻效果.
源代码地址：http://www.eoeandroid.com/thread-176490-1-1.html

//图片冰冻效果
private void IceImage()
{int width = bmp.getWidth();int height = bmp.getHeight();Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);int pixColor = 0;int pixR = 0;int pixG = 0;int pixB = 0;int newColor = 0;int newR = 0;int newG = 0;int newB =0;int[] pixels = new int[width * height];bmp.getPixels(pixels, 0, width, 0, 0, width, height);for (int i = 0; i < height; i++){for (int k = 0; k < width; k++){//获取前一个像素颜色pixColor = pixels[width * i + k];   pixR = Color.red(pixColor);pixG = Color.green(pixColor);pixB = Color.blue(pixColor);//红色newColor = pixR - pixG - pixB;newColor = newColor * 3 / 2;if(newColor < 0) {newColor = -newColor;}if(newColor >255) {newColor = 255;}newR = newColor;//绿色newColor = pixG - pixB - pixR;newColor = newColor * 3 / 2;if(newColor < 0) {newColor = -newColor;}if(newColor >255) {newColor = 255;}newG = newColor;//蓝色newColor = pixB - pixG - pixR;newColor = newColor * 3 / 2;if(newColor < 0) {newColor = -newColor;}if(newColor >255) {newColor = 255;}newB = newColor;pixels[width * i + k] = Color.argb(255, newR, newG, newB);}}bitmap.setPixels(pixels, 0, width, 0, 0, width, height);imageShow.setImageBitmap(bitmap);
}

下面这个代码是CSDN的xu_fu博主的素描处理,对我软件有用.
源代码地址：http://blog.csdn.net/xu_fu/article/details/21485461
效果显示如下图所示,在Menu选择中调用函数IceImage或SuMiaoImage即可实现.

//素描效果
private void SuMiaoImage()
{//创建新Bitmapint width = bmp.getWidth();  int height = bmp.getHeight();  int[] pixels = new int[width * height];    //存储变换图像int[] linpix = new int[width * height];     //存储灰度图像Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565);  bmp.getPixels(pixels, 0, width, 0, 0, width, height);int pixColor = 0;int pixR = 0;int pixG = 0;int pixB = 0;int newR = 0;  int newG = 0;  int newB = 0;//灰度图像for (int i = 1; i < width - 1; i++)  {  for (int j = 1; j < height - 1; j++)   //拉普拉斯算子模板 { 0, -1, 0, -1, -5, -1, 0, -1, 0 {  //获取前一个像素颜色pixColor = pixels[width * i + j];   pixR = Color.red(pixColor);pixG = Color.green(pixColor);pixB = Color.blue(pixColor);//灰度图像int gray=(int)(0.3*pixR+0.59*pixG+0.11*pixB);linpix[width * i + j] = Color.argb(255, gray, gray, gray);//图像反向gray=255-gray;pixels[width * i + j] = Color.argb(255, gray, gray, gray);}}int radius = Math.min(width/2, height/2);int[] copixels = gaussBlur(pixels, width, height, 10, 10/3);   //高斯模糊 采用半径10int[] result = colorDodge(linpix, copixels);   //素描图像 颜色减淡bitmap.setPixels(result, 0, width, 0, 0, width, height);imageShow.setImageBitmap(bitmap);
}//高斯模糊
public static int[] gaussBlur(int[] data, int width, int height, int radius,  float sigma) {  float pa = (float) (1 / (Math.sqrt(2 * Math.PI) * sigma));  float pb = -1.0f / (2 * sigma * sigma);  // generate the Gauss Matrix   float[] gaussMatrix = new float[radius * 2 + 1];  float gaussSum = 0f;  for (int i = 0, x = -radius; x <= radius; ++x, ++i) {  float g = (float) (pa * Math.exp(pb * x * x));  gaussMatrix[i] = g;  gaussSum += g;  }  for (int i = 0, length = gaussMatrix.length; i < length; ++i) {  gaussMatrix[i] /= gaussSum;  }  // x direction   for (int y = 0; y < height; ++y) {  for (int x = 0; x < width; ++x) {  float r = 0, g = 0, b = 0;  gaussSum = 0;  for (int j = -radius; j <= radius; ++j) {  int k = x + j;  if (k >= 0 && k < width) {  int index = y * width + k;  int color = data[index];  int cr = (color & 0x00ff0000) >> 16;  int cg = (color & 0x0000ff00) >> 8;  int cb = (color & 0x000000ff);  r += cr * gaussMatrix[j + radius];  g += cg * gaussMatrix[j + radius];  b += cb * gaussMatrix[j + radius];  gaussSum += gaussMatrix[j + radius];  }  }  int index = y * width + x;  int cr = (int) (r / gaussSum);  int cg = (int) (g / gaussSum);  int cb = (int) (b / gaussSum);  data[index] = cr << 16 | cg << 8 | cb | 0xff000000;  }  }  // y direction   for (int x = 0; x < width; ++x) {  for (int y = 0; y < height; ++y) {  float r = 0, g = 0, b = 0;  gaussSum = 0;  for (int j = -radius; j <= radius; ++j) {  int k = y + j;  if (k >= 0 && k < height) {  int index = k * width + x;  int color = data[index];  int cr = (color & 0x00ff0000) >> 16;  int cg = (color & 0x0000ff00) >> 8;  int cb = (color & 0x000000ff);  r += cr * gaussMatrix[j + radius];  g += cg * gaussMatrix[j + radius];  b += cb * gaussMatrix[j + radius];  gaussSum += gaussMatrix[j + radius];  }  }  int index = y * width + x;  int cr = (int) (r / gaussSum);  int cg = (int) (g / gaussSum);  int cb = (int) (b / gaussSum);  data[index] = cr << 16 | cg << 8 | cb | 0xff000000;  }  }  return data;
}  //颜色减淡
public static int[] colorDodge(int[] baseColor, int[] mixColor) {  for (int i = 0, length = baseColor.length; i < length; ++i) {  int bColor = baseColor[i];  int br = (bColor & 0x00ff0000) >> 16;  int bg = (bColor & 0x0000ff00) >> 8;  int bb = (bColor & 0x000000ff);  int mColor = mixColor[i];  int mr = (mColor & 0x00ff0000) >> 16;  int mg = (mColor & 0x0000ff00) >> 8;  int mb = (mColor & 0x000000ff);  int nr = colorDodgeFormular(br, mr);  int ng = colorDodgeFormular(bg, mg);  int nb = colorDodgeFormular(bb, mb);  baseColor[i] = nr << 16 | ng << 8 | nb | 0xff000000;  }  return baseColor;
}  private static int colorDodgeFormular(int base, int mix) {  int result = base + (base * mix) / (255 - mix);  result = result > 255 ? 255 : result;  return result;  }

最后希望文章对大家有所帮助,感谢上面提到的作者,同时可能还有些如LOMO等效果可参考下面的文章,它是图像处理的一个集合超链接.后面会写PopupWindows实现美图秀秀的效果和对人脸进行处理.
源代码下载：
(By:Eastmount 2014-11-2 晚8点 http://blog.csdn.net/eastmount/)