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