演算法：

一、簡單演算法：將畫素點周圍八個點包括自身一共九個點的RGB值分別相加後平均，作為當前畫素點的RGB值，即可實現效果。

舉例：

ABC

DEF

GHI

假如當前點是E，那麼會有：

1. E.r = (A.r + B.r + C.r + D.r + E.r + F.r + G.r + H.r + I.r) /9// r表示的是E畫素點RGB值的R值

E畫素點的GB值類似。

二、採用高斯模糊：

高斯矩陣：

1. int[] gauss = newint[] { 1, 2, 1, 2, 4, 2, 1, 2, 1 }; 

舉例：（還是上面的九個點）
假如當前點是E，那麼會有：

1. int delta = 16; 
2. E.r =( A.r * gauss[0
   ] + B.r * gauss[1] + C.r * gauss[2] + D.r * gauss[3] + E.r * gauss[4] + F.r * gauss[5] + G.r * gauss[6] + H.r * gauss[7] + I.r * gauss[8]) / delta 

原圖片：

處理後：

兩種處理方式的程式碼：

1. /**
2.      * 模糊效果
3.      * @param bmp
4.      * @return
5.      */
6.     private Bitmap blurImage(Bitmap bmp) 
7.     { 
8.         int width = bmp.getWidth(); 
9.         int height = bmp.getHeight(); 
10.         Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565); 
11.         int pixColor = 0; 
12.         int newR = 0; 
13.         int newG = 0; 
14.         int newB = 0; 
15.         int newColor = 0; 
16.         int[][] colors = newint[9][3]; 
17.         for (int i = 1, length = width - 1; i < length; i++) 
18.         { 
19.             for (int k = 1, len = height - 1; k < len; k++) 
20.             { 
21.                 for (int m = 0; m < 9; m++) 
22.                 { 
23.                     int s = 0; 
24.                     int p = 0; 
25.                     switch(m) 
26.                     { 
27.                     case0: 
28.                         s = i - 1; 
29.                         p = k - 1; 
30.                         break; 
31.                     case1: 
32.                         s = i; 
33.                         p = k - 1; 
34.                         break; 
35.                     case2: 
36.                         s = i + 1; 
37.                         p = k - 1; 
38.                         break; 
39.                     case3: 
40.                         s = i + 1; 
41.                         p = k; 
42.                         break; 
43.                     case4: 
44.                         s = i + 1; 
45.                         p = k + 1; 
46.                         break; 
47.                     case5: 
48.                         s = i; 
49.                         p = k + 1; 
50.                         break; 
51.                     case6: 
52.                         s = i - 1; 
53.                         p = k + 1; 
54.                         break; 
55.                     case7: 
56.                         s = i - 1; 
57.                         p = k; 
58.                         break; 
59.                     case8: 
60.                         s = i; 
61.                         p = k; 
62.                     } 
63.                     pixColor = bmp.getPixel(s, p); 
64.                     colors[m][0] = Color.red(pixColor); 
65.                     colors[m][1] = Color.green(pixColor); 
66.                     colors[m][2] = Color.blue(pixColor); 
67.                 } 
68.                 for (int m = 0; m < 9; m++) 
69.                 { 
70.                     newR += colors[m][0]; 
71.                     newG += colors[m][1]; 
72.                     newB += colors[m][2]; 
73.                 } 
74.                 newR = (int) (newR / 9F); 
75.                 newG = (int) (newG / 9F); 
76.                 newB = (int) (newB / 9F); 
77.                 newR = Math.min(255, Math.max(0, newR)); 
78.                 newG = Math.min(255, Math.max(0, newG)); 
79.                 newB = Math.min(255, Math.max(0, newB)); 
80.                 newColor = Color.argb(255, newR, newG, newB); 
81.                 bitmap.setPixel(i, k, newColor); 
82.                 newR = 0; 
83.                 newG = 0; 
84.                 newB = 0; 
85.             } 
86.         } 
87.         return bitmap; 
88.     } 
89.     /**
90.      * 柔化效果(高斯模糊)(優化後比上面快三倍)
91.      * @param bmp
92.      * @return
93.      */
94.     private Bitmap blurImageAmeliorate(Bitmap bmp) 
95.     { 
96.         long start = System.currentTimeMillis(); 
97.         // 高斯矩陣
98.         int[] gauss = newint[] { 1, 2, 1, 2, 4, 2, 1, 2, 1 }; 
99.         int width = bmp.getWidth(); 
100.         int height = bmp.getHeight(); 
101.         Bitmap bitmap = Bitmap.createBitmap(width, height, Bitmap.Config.RGB_565); 
102.         int pixR = 0; 
103.         int pixG = 0; 
104.         int pixB = 0; 
105.         int pixColor = 0; 
106.         int newR = 0; 
107.         int newG = 0; 
108.         int newB = 0; 
109.         int delta = 16; // 值越小圖片會越亮，越大則越暗
110.         int idx = 0; 
111.         int[] pixels = newint[width * height]; 
112.         bmp.getPixels(pixels, 0, width, 0, 0, width, height); 
113.         for (int i = 1, length = height - 1; i < length; i++) 
114.         { 
115.             for (int k = 1, len = width - 1; k < len; k++) 
116.             { 
117.                 idx = 0; 
118.                 for (int m = -1; m <= 1; m++) 
119.                 { 
120.                     for (int n = -1; n <= 1; n++) 
121.                     { 
122.                         pixColor = pixels[(i + m) * width + k + n]; 
123.                         pixR = Color.red(pixColor); 
124.                         pixG = Color.green(pixColor); 
125.                         pixB = Color.blue(pixColor); 
126.                         newR = newR + (int) (pixR * gauss[idx]); 
127.                         newG = newG + (int) (pixG * gauss[idx]); 
128.                         newB = newB + (int) (pixB * gauss[idx]); 
129.                         idx++; 
130.                     } 
131.                 } 
132.                 newR /= delta; 
133.                 newG /= delta; 
134.                 newB /= delta; 
135.                 newR = Math.min(255, Math.max(0, newR)); 
136.                 newG = Math.min(255, Math.max(0, newG)); 
137.                 newB = Math.min(255, Math.max(0, newB)); 
138.                 pixels[i * width + k] = Color.argb(255, newR, newG, newB); 
139.                 newR = 0; 
140.                 newG = 0; 
141.                 newB = 0; 
142.             } 
143.         } 
144.         bitmap.setPixels(pixels, 0, width, 0, 0, width, height); 
145.         long end = System.currentTimeMillis(); 
146.         Log.d("may", "used time="+(end - start)); 
147.         return bitmap; 
148.     } 

在優化後的程式碼中要注意了，pixels陣列不能超過規定的大小，也就是說圖片的尺寸不能太大，否則會棧記憶體溢位。