html5利用canvas实现图片转素描效果

素描滤镜原理：
最基础的算法就是：
1、去色；（去色公式：gray = 0.3 red + 0.59 green + 0.11 * blue）
2、复制去色图层，并且反色；
3、对反色图像进行高斯模糊；
4、模糊后的图像叠加模式选择颜色减淡效果。
减淡公式：C =MIN( A +（A×B）/（255-B）,255)，其中C为混合结果，A为去色后的像素点，B为高斯模糊后的像素点。

先看看效果对比图：

sigma可以调节效果。

代码实例：

 !DOCTYPE html  html  head  meta charset= UTF-8  title /title  /head  body  div id= controls  input type= file name= id= imgs value= /  br /  !-- input type= range name= id= range_radius value= 10 oninput= changeRadius() /  radius： span id= value_radius 1 /span  br / --  input type= range name= id= range_sigma value= 40 oninput= changeSigma() /  sigma： span id= value_sigma 0.8 /span  br /  a href= download= canvas_love.png id= save_href 下载 /a  /div  canvas id= canvas1 width= height= /canvas  canvas id= canvas2 width= height= /canvas  script type= text/javascript  var eleImg = document.getElementById( imgs  var eleRadius = document.getElementById( range_radius  var eleSigma = document.getElementById( range_sigma  var valueRadius = document.getElementById( value_radius  var valueSigma = document.getElementById( value_sigma  var svaeHref = document.getElementById( save_href  var imgSrc = img/2.jpg  var radius = 1; var sigma = 0.8; eleImg.addEventListener( input ,function (e) { var fileObj = e.currentTarget.files[0] if (window.FileReader) {  var reader = new FileReader();  reader.readAsDataURL(fileObj);  //监听文件读取结束后事件  reader.onloadend = function (e) { imgSrc = e.target.result; //e.target.result就是最后的路径地址 sketch() var butSave = document.getElementById( save  function changeRadius() { valueRadius.innerText = eleRadius.value/10; radius = eleRadius.value/10; sketch() function changeSigma() { valueSigma.innerText = eleSigma.value/50; sigma = eleSigma.value/50; sketch() var canvas1 = document.querySelector( #canvas1  var cxt1 = canvas1.getContext( 2d  var canvas = document.querySelector( #canvas2  var cxt = canvas.getContext( 2d  function sketch() { cxt1.clearRect(0,0,canvas1.width,canvas1.height);  cxt.clearRect(0,0,canvas.width,canvas.height);  var img = new Image(); img.src = imgSrc; img.onload = function () { canvas1.width = 600; canvas1.height = (img.height/img.width)*600; cxt1.drawImage(img, 0, 0, canvas1.width, canvas1.height); canvas.width = 600; canvas.height = (img.height/img.width)*600; cxt.drawImage(img, 0, 0, canvas.width, canvas.height); var imageData = cxt.getImageData(0, 0, canvas.width, canvas.height); //对于 ImageData 对象中的每个像素，都存在着四方面的信息，即 RGBA 值 var imageData_length = imageData.data.length/4;// var originData = JSON.parse(JSON.stringify(imageData)) // 解析之后进行算法运算 var originData = []; for (var i = 0; i imageData_length; i++) { var red = imageData.data[i*4]; var green = imageData.data[i*4 + 1]; var blue = imageData.data[i*4 + 2]; var gray = 0.3 * red + 0.59 * green + 0.11 * blue;//去色 originData.push(gray) originData.push(gray) originData.push(gray) originData.push(imageData.data[i * 4 + 3]) var anti_data = 255 - gray;//取反 imageData.data[i * 4] = anti_data; imageData.data[i * 4 + 1] = anti_data; imageData.data[i * 4 + 2] = anti_data; imageData = gaussBlur(imageData, radius, sigma)//高斯模糊 for (var i = 0; i imageData_length; i++) { var dodge_data = Math.min((originData[i*4] + (originData[i*4]*imageData.data[i * 4])/(255-imageData.data[i * 4])), 255)//减淡 imageData.data[i * 4] = dodge_data; imageData.data[i * 4 + 1] = dodge_data; imageData.data[i * 4 + 2] = dodge_data; console.log(imageData) cxt.putImageData(imageData, 0, 0); var tempSrc = canvas.toDataURL( image/png  svaeHref.href=tempSrc; sketch() function gaussBlur(imgData, radius, sigma) { var pixes = imgData.data, width = imgData.width, height = imgData.height; radius = radius || 5; sigma = sigma || radius / 3; var gaussEdge = radius * 2 + 1; // 高斯矩阵的边长 var gaussMatrix = [], gaussSum = 0, a = 1 / (2 * sigma * sigma * Math.PI), b = -a * Math.PI; for (var i=-radius; i =radius; i++) { for (var j=-radius; j =radius; j++) { var gxy = a * Math.exp((i * i + j * j) * b); gaussMatrix.push(gxy); gaussSum += gxy; // 得到高斯矩阵的和，用来归一化 var gaussNum = (radius + 1) * (radius + 1); for (var i=0; i gaussNum; i++) { gaussMatrix[i] = gaussMatrix[i] / gaussSum; // 除gaussSum是归一化 //console.log(gaussMatrix); // 循环计算整个图像每个像素高斯处理之后的值 for (var x=0; x width;x++) { for (var y=0; y height; y++) { var r = 0, g = 0, b = 0; //console.log(1); // 计算每个点的高斯处理之后的值 for (var i=-radius; i =radius; i++) { // 处理边缘 var m = handleEdge(i, x, width); for (var j=-radius; j =radius; j++) { // 处理边缘 var mm = handleEdge(j, y, height); var currentPixId = (mm * width + m) * 4; var jj = j + radius; var ii = i + radius; r += pixes[currentPixId] * gaussMatrix[jj * gaussEdge + ii]; g += pixes[currentPixId + 1] * gaussMatrix[jj * gaussEdge + ii]; b += pixes[currentPixId + 2] * gaussMatrix[jj * gaussEdge + ii]; var pixId = (y * width + x) * 4; pixes[pixId] = ~~r; pixes[pixId + 1] = ~~g; pixes[pixId + 2] = ~~b; imgData.data = pixes; return imgData; function handleEdge(i, x, w) { var m = x + i; if (m 0) { m = -m; } else if (m = w) { m = w + i - x; return m; /script  /body  /html 

上面就是canvas实现图片转素描效果的全部代码，大家可以自己动手编译调试。

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