用canvas实现图片滤镜效果详解之视频效果
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
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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);
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2.设置过滤矩阵
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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 ];
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3.获取过滤数据
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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;
}
}
}
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4.写入过滤后的数据
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context.putImageData(canvasData, 0, 0);
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5.效果预览
点击这里预览
5.参考资料
代震军ImageFilter开源项目