HTML5 Canvas 调整大小(缩小)图像质量?

2022-01-17 00:00:00 canvas javascript html css html5-canvas

我使用 html5 画布元素在我的浏览器中调整图像大小.事实证明,质量非常低.我发现了这个:和
小提琴本身:http://jsfiddle.net/gamealchemist/r6aVp/

//以(float) scale < 缩放图像1//返回一个包含缩放图像的画布.函数 downScaleImage(img, scale) {var imgCV = document.createElement('canvas');imgCV.width = img.width;imgCV.height = img.height;var imgCtx = imgCV.getContext('2d');imgCtx.drawImage(img, 0, 0);返回 downScaleCanvas(imgCV, scale);}//按 (float) scale < 缩放画布1//返回一个包含缩放图像的新画布.功能 downScaleCanvas(cv, scale) {if (!(scale < 1) || !(scale > 0)) throw ('scale 必须是正数 <1');var sqScale = 比例 * 比例;//平方比例 = 目标内源像素的面积var sw = cv.width;//源图像宽度var sh = cv.height;//源图像高度var tw = Math.floor(sw * scale);//目标图像宽度var th = Math.floor(sh * scale);//目标图像高度var sx = 0,sy = 0,sIndex = 0;//源 x,y,源数组中的索引var tx = 0, ty = 0, yIndex = 0, tIndex = 0;//目标数组中的目标 x,y, x,y 索引变量 tX = 0, tY = 0;//四舍五入的 tx, ty变量 w = 0, nw = 0, wx = 0, nwx = 0, wy = 0, nwy = 0;//重量/下一个重量 x/y//weight 是目标中当前源点的权重.//下一个权重是当前源点在下一个目标点内的权重.变量 crossX = 假;//缩放后的 px 是否越过其当前的 px 右边框?变量 crossY = 假;//缩放后的 px 是否越过其当前的 px 底部边框?var sBuffer = cv.getContext('2d').getImageData(0, 0, sw, sh).data;//源缓冲区 8 位 rgbavar tBuffer = new Float32Array(3 * tw * th);//目标缓冲区 Float32 rgbvar sR = 0,sG = 0,sB = 0;//源的当前点 r,g,b/* 未经测试!var sA = 0;//源阿尔法*/对于 (sy = 0; sy < sh; sy++) {ty = sy * 比例;//y src 在目标中的位置tY = 0 |ty;//四舍五入:目标像素的 yyIndex = 3 * tY * tw;//目标数组中的行索引crossY = (tY != (0 | ty + scale));if (crossY) {//如果像素穿过底部目标像素wy = (tY + 1 - ty);//目标像素内点的权重nwy = (ty + scale - tY - 1);//... 在 y+1 目标像素内}for (sx = 0; sx 

这是相当内存贪婪,因为需要一个浮点缓冲区来存储目标图像的中间值(-> 如果我们计算结果画布,我们使用源图像的 6 倍内存这个算法).
它也很昂贵,因为无论目标大小如何都使用每个源像素,而且我们必须为 getImageData/putImageDate 付费,而且速度也很慢.
但是在这种情况下,没有办法比处理每个源值更快,而且情况还不错:对于我的 740 * 556 袋熊图像,处理需要 30 到 40 毫秒.

I use html5 canvas elements to resize images im my browser. It turns out that the quality is very low. I found this: Disable Interpolation when Scaling a <canvas> but it does not help to increase the quality.

Below is my css and js code as well as the image scalled with Photoshop and scaled in the canvas API.

What do I have to do to get optimal quality when scaling an image in the browser?

Note: I want to scale down a large image to a small one, modify color in a canvas and send the result from the canvas to the server.

CSS:

canvas, img {
    image-rendering: optimizeQuality;
    image-rendering: -moz-crisp-edges;
    image-rendering: -webkit-optimize-contrast;
    image-rendering: optimize-contrast;
    -ms-interpolation-mode: nearest-neighbor;
}

JS:

var $img = $('<img>');
var $originalCanvas = $('<canvas>');
$img.load(function() {


   var originalContext = $originalCanvas[0].getContext('2d');   
   originalContext.imageSmoothingEnabled = false;
   originalContext.webkitImageSmoothingEnabled = false;
   originalContext.mozImageSmoothingEnabled = false;
   originalContext.drawImage(this, 0, 0, 379, 500);
});

The image resized with photoshop:

The image resized on canvas:

Edit:

I tried to make downscaling in more than one steps as proposed in:

Resizing an image in an HTML5 canvas and Html5 canvas drawImage: how to apply antialiasing

This is the function I have used:

function resizeCanvasImage(img, canvas, maxWidth, maxHeight) {
    var imgWidth = img.width, 
        imgHeight = img.height;

    var ratio = 1, ratio1 = 1, ratio2 = 1;
    ratio1 = maxWidth / imgWidth;
    ratio2 = maxHeight / imgHeight;

    // Use the smallest ratio that the image best fit into the maxWidth x maxHeight box.
    if (ratio1 < ratio2) {
        ratio = ratio1;
    }
    else {
        ratio = ratio2;
    }

    var canvasContext = canvas.getContext("2d");
    var canvasCopy = document.createElement("canvas");
    var copyContext = canvasCopy.getContext("2d");
    var canvasCopy2 = document.createElement("canvas");
    var copyContext2 = canvasCopy2.getContext("2d");
    canvasCopy.width = imgWidth;
    canvasCopy.height = imgHeight;  
    copyContext.drawImage(img, 0, 0);

    // init
    canvasCopy2.width = imgWidth;
    canvasCopy2.height = imgHeight;        
    copyContext2.drawImage(canvasCopy, 0, 0, canvasCopy.width, canvasCopy.height, 0, 0, canvasCopy2.width, canvasCopy2.height);


    var rounds = 2;
    var roundRatio = ratio * rounds;
    for (var i = 1; i <= rounds; i++) {
        console.log("Step: "+i);

        // tmp
        canvasCopy.width = imgWidth * roundRatio / i;
        canvasCopy.height = imgHeight * roundRatio / i;

        copyContext.drawImage(canvasCopy2, 0, 0, canvasCopy2.width, canvasCopy2.height, 0, 0, canvasCopy.width, canvasCopy.height);

        // copy back
        canvasCopy2.width = imgWidth * roundRatio / i;
        canvasCopy2.height = imgHeight * roundRatio / i;
        copyContext2.drawImage(canvasCopy, 0, 0, canvasCopy.width, canvasCopy.height, 0, 0, canvasCopy2.width, canvasCopy2.height);

    } // end for


    // copy back to canvas
    canvas.width = imgWidth * roundRatio / rounds;
    canvas.height = imgHeight * roundRatio / rounds;
    canvasContext.drawImage(canvasCopy2, 0, 0, canvasCopy2.width, canvasCopy2.height, 0, 0, canvas.width, canvas.height);


}

Here is the result if I use a 2 step down sizing:

Here is the result if I use a 3 step down sizing:

Here is the result if I use a 4 step down sizing:

Here is the result if I use a 20 step down sizing:

Note: It turns out that from 1 step to 2 steps there is a large improvement in image quality but the more steps you add to the process the more fuzzy the image becomes.

Is there a way to solve the problem that the image gets more fuzzy the more steps you add?

Edit 2013-10-04: I tried the algorithm of GameAlchemist. Here is the result compared to Photoshop.

PhotoShop Image:

GameAlchemist's Algorithm:

解决方案

Since your problem is to downscale your image, there is no point in talking about interpolation -which is about creating pixel-. The issue here is downsampling.

To downsample an image, we need to turn each square of p * p pixels in the original image into a single pixel in the destination image.

For performances reasons Browsers do a very simple downsampling : to build the smaller image, they will just pick ONE pixel in the source and use its value for the destination. which 'forgets' some details and adds noise.

Yet there's an exception to that : since the 2X image downsampling is very simple to compute (average 4 pixels to make one) and is used for retina/HiDPI pixels, this case is handled properly -the Browser does make use of 4 pixels to make one-.

BUT... if you use several time a 2X downsampling, you'll face the issue that the successive rounding errors will add too much noise.
What's worse, you won't always resize by a power of two, and resizing to the nearest power + a last resizing is very noisy.

What you seek is a pixel-perfect downsampling, that is : a re-sampling of the image that will take all input pixels into account -whatever the scale-.
To do that we must compute, for each input pixel, its contribution to one, two, or four destination pixels depending wether the scaled projection of the input pixels is right inside a destination pixels, overlaps an X border, an Y border, or both.
( A scheme would be nice here, but i don't have one. )

Here's an example of canvas scale vs my pixel perfect scale on a 1/3 scale of a zombat.

Notice that the picture might get scaled in your Browser, and is .jpegized by S.O..
Yet we see that there's much less noise especially in the grass behind the wombat, and the branches on its right. The noise in the fur makes it more contrasted, but it looks like he's got white hairs -unlike source picture-.
Right image is less catchy but definitively nicer.

Here's the code to do the pixel perfect downscaling :

fiddle result : http://jsfiddle.net/gamealchemist/r6aVp/embedded/result/
fiddle itself : http://jsfiddle.net/gamealchemist/r6aVp/

// scales the image by (float) scale < 1
// returns a canvas containing the scaled image.
function downScaleImage(img, scale) {
    var imgCV = document.createElement('canvas');
    imgCV.width = img.width;
    imgCV.height = img.height;
    var imgCtx = imgCV.getContext('2d');
    imgCtx.drawImage(img, 0, 0);
    return downScaleCanvas(imgCV, scale);
}

// scales the canvas by (float) scale < 1
// returns a new canvas containing the scaled image.
function downScaleCanvas(cv, scale) {
    if (!(scale < 1) || !(scale > 0)) throw ('scale must be a positive number <1 ');
    var sqScale = scale * scale; // square scale = area of source pixel within target
    var sw = cv.width; // source image width
    var sh = cv.height; // source image height
    var tw = Math.floor(sw * scale); // target image width
    var th = Math.floor(sh * scale); // target image height
    var sx = 0, sy = 0, sIndex = 0; // source x,y, index within source array
    var tx = 0, ty = 0, yIndex = 0, tIndex = 0; // target x,y, x,y index within target array
    var tX = 0, tY = 0; // rounded tx, ty
    var w = 0, nw = 0, wx = 0, nwx = 0, wy = 0, nwy = 0; // weight / next weight x / y
    // weight is weight of current source point within target.
    // next weight is weight of current source point within next target's point.
    var crossX = false; // does scaled px cross its current px right border ?
    var crossY = false; // does scaled px cross its current px bottom border ?
    var sBuffer = cv.getContext('2d').
    getImageData(0, 0, sw, sh).data; // source buffer 8 bit rgba
    var tBuffer = new Float32Array(3 * tw * th); // target buffer Float32 rgb
    var sR = 0, sG = 0,  sB = 0; // source's current point r,g,b
    /* untested !
    var sA = 0;  //source alpha  */    

    for (sy = 0; sy < sh; sy++) {
        ty = sy * scale; // y src position within target
        tY = 0 | ty;     // rounded : target pixel's y
        yIndex = 3 * tY * tw;  // line index within target array
        crossY = (tY != (0 | ty + scale)); 
        if (crossY) { // if pixel is crossing botton target pixel
            wy = (tY + 1 - ty); // weight of point within target pixel
            nwy = (ty + scale - tY - 1); // ... within y+1 target pixel
        }
        for (sx = 0; sx < sw; sx++, sIndex += 4) {
            tx = sx * scale; // x src position within target
            tX = 0 |  tx;    // rounded : target pixel's x
            tIndex = yIndex + tX * 3; // target pixel index within target array
            crossX = (tX != (0 | tx + scale));
            if (crossX) { // if pixel is crossing target pixel's right
                wx = (tX + 1 - tx); // weight of point within target pixel
                nwx = (tx + scale - tX - 1); // ... within x+1 target pixel
            }
            sR = sBuffer[sIndex    ];   // retrieving r,g,b for curr src px.
            sG = sBuffer[sIndex + 1];
            sB = sBuffer[sIndex + 2];

            /* !! untested : handling alpha !!
               sA = sBuffer[sIndex + 3];
               if (!sA) continue;
               if (sA != 0xFF) {
                   sR = (sR * sA) >> 8;  // or use /256 instead ??
                   sG = (sG * sA) >> 8;
                   sB = (sB * sA) >> 8;
               }
            */
            if (!crossX && !crossY) { // pixel does not cross
                // just add components weighted by squared scale.
                tBuffer[tIndex    ] += sR * sqScale;
                tBuffer[tIndex + 1] += sG * sqScale;
                tBuffer[tIndex + 2] += sB * sqScale;
            } else if (crossX && !crossY) { // cross on X only
                w = wx * scale;
                // add weighted component for current px
                tBuffer[tIndex    ] += sR * w;
                tBuffer[tIndex + 1] += sG * w;
                tBuffer[tIndex + 2] += sB * w;
                // add weighted component for next (tX+1) px                
                nw = nwx * scale
                tBuffer[tIndex + 3] += sR * nw;
                tBuffer[tIndex + 4] += sG * nw;
                tBuffer[tIndex + 5] += sB * nw;
            } else if (crossY && !crossX) { // cross on Y only
                w = wy * scale;
                // add weighted component for current px
                tBuffer[tIndex    ] += sR * w;
                tBuffer[tIndex + 1] += sG * w;
                tBuffer[tIndex + 2] += sB * w;
                // add weighted component for next (tY+1) px                
                nw = nwy * scale
                tBuffer[tIndex + 3 * tw    ] += sR * nw;
                tBuffer[tIndex + 3 * tw + 1] += sG * nw;
                tBuffer[tIndex + 3 * tw + 2] += sB * nw;
            } else { // crosses both x and y : four target points involved
                // add weighted component for current px
                w = wx * wy;
                tBuffer[tIndex    ] += sR * w;
                tBuffer[tIndex + 1] += sG * w;
                tBuffer[tIndex + 2] += sB * w;
                // for tX + 1; tY px
                nw = nwx * wy;
                tBuffer[tIndex + 3] += sR * nw;
                tBuffer[tIndex + 4] += sG * nw;
                tBuffer[tIndex + 5] += sB * nw;
                // for tX ; tY + 1 px
                nw = wx * nwy;
                tBuffer[tIndex + 3 * tw    ] += sR * nw;
                tBuffer[tIndex + 3 * tw + 1] += sG * nw;
                tBuffer[tIndex + 3 * tw + 2] += sB * nw;
                // for tX + 1 ; tY +1 px
                nw = nwx * nwy;
                tBuffer[tIndex + 3 * tw + 3] += sR * nw;
                tBuffer[tIndex + 3 * tw + 4] += sG * nw;
                tBuffer[tIndex + 3 * tw + 5] += sB * nw;
            }
        } // end for sx 
    } // end for sy

    // create result canvas
    var resCV = document.createElement('canvas');
    resCV.width = tw;
    resCV.height = th;
    var resCtx = resCV.getContext('2d');
    var imgRes = resCtx.getImageData(0, 0, tw, th);
    var tByteBuffer = imgRes.data;
    // convert float32 array into a UInt8Clamped Array
    var pxIndex = 0; //  
    for (sIndex = 0, tIndex = 0; pxIndex < tw * th; sIndex += 3, tIndex += 4, pxIndex++) {
        tByteBuffer[tIndex] = Math.ceil(tBuffer[sIndex]);
        tByteBuffer[tIndex + 1] = Math.ceil(tBuffer[sIndex + 1]);
        tByteBuffer[tIndex + 2] = Math.ceil(tBuffer[sIndex + 2]);
        tByteBuffer[tIndex + 3] = 255;
    }
    // writing result to canvas.
    resCtx.putImageData(imgRes, 0, 0);
    return resCV;
}

It is quite memory greedy, since a float buffer is required to store the intermediate values of the destination image (-> if we count the result canvas, we use 6 times the source image's memory in this algorithm).
It is also quite expensive, since each source pixel is used whatever the destination size, and we have to pay for the getImageData / putImageDate, quite slow also.
But there's no way to be faster than process each source value in this case, and situation is not that bad : For my 740 * 556 image of a wombat, processing takes between 30 and 40 ms.

相关文章