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);

　　

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 ];

　　

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;                }             }        }

　　

4.写入过滤后的数据

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1	context.putImageData(canvasData, 0, 0);

　　

5.效果预览

点击这里预览

5.参考资料

代震军ImageFilter开源项目