用canvas实现图片滤镜效果详解之视频效果_程序开发

用canvas实现图片滤镜效果详解之视频效果

admin

2023-02-11 01:20:11

0次

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

123456 img.src = ’http://bloglaotou.duapp.com/wp-content/themes/frontopen2/tools/filter/p_w_picpath3.jpg’; canvas.width = img.width; canvas.height = img.height; varcontext = canvas.getContext(“2d”); context.drawImage(img, 0, 0); varcanvasData = context.getImageData(0, 0, canvas.width, canvas.height);

2.设置过滤矩阵

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960 varm_VideoType=0; varpattern=newArray(); 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; } } varpattern_width = [ 2, 1, 3, 5 ]; varpattern_height = [6, 3, 3, 15 ];

3.获取过滤数据

12345678910111213141516171819202122232425262728293031323334 for( varx = 0; x < canvasData.width; x++) { for( vary = 0; y < canvasData.height; y++) { // Index of the pixel in the array varidx = (x + y * canvasData.width) * 4; varr = canvasData.data[idx + 0]; varg = canvasData.data[idx + 1]; varb = canvasData.data[idx + 2]; varnWidth = pattern_width[m_VideoType]; varnHeight = pattern_height[m_VideoType]; varindex = nWidth * (y % nHeight) + (x % nWidth); index = pattern[index]; if(index == 0) varr = fclamp0255(2 * r); if(index == 1) varg = fclamp0255(2 * g); if(index == 2) varb = 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

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

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