這是一個很有意思的特效，模擬攝像機拍攝電視屏幕畫面時出現點狀顆粒的效果。顆粒的大小通過變換矩陣實現，可以任意調節，有興趣研究的朋友可以嘗試更多的效果，代碼沒有經過優化，只是一個粗糙的Demo，大家可以自行改進。
1.獲取圖像數據
1 2 3 4 5 6 | img.src = ’http://bloglaotou.duapp.com/wp-content/themes/frontopen2/tools/filter/image2.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.設置過濾矩陣
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 | 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.獲取過濾數據
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( 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 // 加上黑色的邊框 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.寫入過濾後的數據
1 | context.putImageData(canvasData, 0, 0); |
5.效果預覽
點擊這裏預覽