[Android] 通过Menu实现图片怀旧、浮雕、模糊、光照和素描效果

    因为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,这里先简介怎样通过Menu实现打开相冊中的图片、怀旧效果、浮雕效果、光照效果和素描效果.后面可能会讲述怎样通过PopupWindow实现自己定义的Menu效果.

    希望文章对大家有所帮助,假设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,能够包括自己定义的图片和文字.假设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全部选项.

    以下讲述怎样在Android 4.0项目中实现简单的Menu功能.加入例如以下代码：

@Override
public boolean onCreateOptionsMenu(Menu menu) { //创建Menu
	//自己定义menu 加入图标(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;
}

   因为Android 4.0系统缺省UI风格有所变化,所以须要设置Activity的theme为Theme.Light.同一时候也能够在res/menu/main.xml设置菜单项.參考"恺风"博主关于Menu的介绍,很不错.http://blog.csdn.net/flowingflying/article/details/11967301

<activity
    android: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,同一时候我调用的图标都是Android自带的图片,用户也能够自己定义.(

url=tt6IgAjYh9ylTNsbYPTslH-sBz0vYfncK4MwssMOGJfzx0NBbjGvL_4PSK5wtAsxXKj5aw5Z05VM3yrtWp-TbkzVjnHa28oGjiDe2K1Soda">android默认图标列表)

                                       

   
同一时候设置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" >
    <!-- 顶部加入文字 -->
    <RelativeLayout
        android: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 -->
    <RelativeLayout
        android: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">
        <ImageView
	        android: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,通过调用自己定义函数实现各种功能.

@Override
public boolean onOptionsItemSelected(MenuItem item) { //选择Menu
	//选择id 相应Menu.add的參数Menu.FIRST+i
    int 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);
}

   当中打开图片函数实现方法例如以下,而上面的非常多自己定义函数都将在第三部分介绍,你此处能够凝视掉仅仅验证"打开图片".首先加入自己定义变量和获取ImageView布局.

//自己定义变量
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();
    }
}

   
然后通过自己定义函数OpenImage打开函数,与前面文章介绍的方法一样.

//自己定义函数 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 {
           //加载图片尺寸大小没加载图片本身 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
}  

    以下讲讲使用Options Menu的函数：

   onCreateOptionsMenu(Menu
menu)创建options
menu,这个函数仅仅会在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函数实现加入菜单项,如menu.add(Menu.NONE,Menu.FIRST+1,1,"打开"),第一个參数表示组别;第二个參数menu标志编号与onOptionsItemSelected函数中值相应;第三个參数是在菜单中出现的顺序,顺序由小到大,由左至右;第四个參数是显示的文字,同一时候setIcon能够设置图标.

三. 图像各种效果实现

   
最后讲讲各个效果实现过程,通过不同自己定义函数实现.当中各个效果主要參照《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);
}

    显示效果例如以下图所看到的：

                     

2.图片浮雕效果

//图片浮雕处理
//底片效果也很easy: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);
}

   显示效果例如以下图所看到的：

                       

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含自身共九个点RGB值分别相加后平均,当前像素点的RGB值
	 * 复杂算法採用高斯模糊
	 * 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相应项相乘的和,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);
}

   
该图显示效果不是非常理想,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,也能够自己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;
	//环绕圆形光照
	int centerX = width / 2;
	int centerY = height / 2;
	int radius = Math.min(centerX, centerY);
	float strength = 150F;  //光照强度100-150
	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);
			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)
			{
				//依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);
}

    显示效果例如以下图所看到的 

                                                          

5.图片锐化效果

    本打算採用拉普拉斯算子或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,可是Android总是效果不是非常好啊,并且有虚线!网上一些锐化效果全然没有实现显示图像轮廓,与原图差别不大,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);
                    //图像像素与相应摸板相乘
                    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,而右图是我曾经《数字图像处理》课用C++写的不同模版的锐化效果.

           

    以下再介绍些效果,以下这个效果是參考亚瑟BOY的冰冻效果.

    源码地址：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);
}

 
  以下这个代码是CSDN的xu_fu博主的素描处理,对我软件实用.

    源码地址：http://blog.csdn.net/xu_fu/article/details/21485461

      效果显演示样例如以下图所看到的,在Menu选择中调用函数IceImage或SuMiaoImage就可以实现.

                      

//素描效果
private void SuMiaoImage()
{
	//创建新Bitmap
	int 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 採用半径10
    int[] 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,同一时候可能还有些如LOMO等效果可參考以下的文章,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.

    源码下载：

    (By:Eastmount 2014-11-2 晚8点 http://blog.csdn.net/eastmount/)