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

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.效果预览

点击这里预览

5.参考资料

代震军ImageFilter开源项目