用canvas实现图片滤镜效果附演示

这是一个很有意思的特效，模拟摄像机拍摄电视屏幕画面时出现点状颗粒的效果。颗粒的大小通过变换矩阵实现，可以任意调节，有兴趣研究的朋友可以尝试更多的效果，代码没有经过优化，只是一个粗糙的Demo，大家可以自行改进。

1.获取图像数据

img.src = ’http://bloglaotou.duapp.com/wp-content/themes/frontopen2/tools/filter/image2.jpg’; 
canvas.width = img.width; 
canvas.height = img.height; 
var context = canvas.getContext(“2d”); 
context.drawImage(img, 0, 0); 
var canvasData = context.getImageData(0, 0, canvas.width, canvas.height);

2.设置过滤矩阵

var m_VideoType=0; 
var pattern=new Array(); 
switch (m_VideoType) 
{ 
case0://VIDEO_TYPE.VIDEO_STAGGERED: 
{ 
pattern = [ 
0, 1, 
0, 2, 
1, 2, 
1, 0, 
2, 0, 
2, 1, 
]; 
break; 
} 
case1://VIDEO_TYPE.VIDEO_TRIPED: 
{ 
pattern = [ 
0, 
1, 
2, 
]; 
break; 
} 
case2://VIDEO_TYPE.VIDEO_3X3: 
{ 
pattern = 
[ 
0, 1, 2, 
2, 0, 1, 
1, 2, 0, 
]; 
break; 
} 
default: 
{ 
pattern = 
[ 
0, 1, 2, 0, 0, 
1, 1, 1, 2, 0, 
0, 1, 2, 2, 2, 
0, 0, 1, 2, 0, 
0, 1, 1, 1, 2, 
2, 0, 1, 2, 2, 
0, 0, 0, 1, 2, 
2, 0, 1, 1, 1, 
2, 2, 0, 1, 2, 
2, 0, 0, 0, 1, 
1, 2, 0, 1, 1, 
2, 2, 2, 0, 1, 
1, 2, 0, 0, 0, 
1, 1, 2, 0, 1, 
1, 2, 2, 2, 0, 
]; 
break; 
} 
} 
var pattern_width = [ 2, 1, 3, 5 ]; 
var pattern_height = [6, 3, 3, 15 ];

3.获取过滤数据

for ( var x = 0; x < canvasData.width; x++) { 
for ( var y = 0; y < canvasData.height; y++) { 
// Index of the pixel in the array 
var idx = (x + y * canvasData.width) * 4; 
var r = canvasData.data[idx + 0]; 
var g = canvasData.data[idx + 1]; 
var b = canvasData.data[idx + 2]; 
var nWidth = pattern_width[m_VideoType]; 
var nHeight = pattern_height[m_VideoType]; 
var index = nWidth * (y % nHeight) + (x % nWidth); 
index = pattern[index]; 
if (index == 0) 
var r = fclamp0255(2 * r); 
if (index == 1) 
var g = fclamp0255(2 * g); 
if (index == 2) 
var b = fclamp0255(2 * b); 
// assign gray scale value 
canvasData.data[idx + 0] = r; // Red channel 
canvasData.data[idx + 1] = g; // Green channel 
canvasData.data[idx + 2] = b; // Blue channel 
canvasData.data[idx + 3] = 255; // Alpha channel 
// 加上黑色的边框 
if(x < 8 || y < 8 || x > (canvasData.width - 8) || y > (canvasData.height - 8)) 
{ 
canvasData.data[idx + 0] = 0; 
canvasData.data[idx + 1] = 0; 
canvasData.data[idx + 2] = 0; 
} 
} 
}

4.写入过滤后的数据

context.putImageData(canvasData, 0, 0);

5.参考资料
代震军ImageFilter开源项目