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
1 2 3 4 5 6 | img.src = ’http: //bloglaotou.duapp.com/wp-content/themes/frontopen2/tools/filter/p_w_picpath2.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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | 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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | 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
1 | context.putImageData(canvasData, 0, 0); |
5.效果预览
点击预览