Merge pull request #1797 from tschaub/convolution-kernel
Example applying a convolution kernel to an image.
This commit is contained in:
Tim Schaub
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examples/image-filter.html
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65
examples/image-filter.html
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<!doctype html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<meta http-equiv="X-UA-Compatible" content="chrome=1">
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<meta name="viewport" content="initial-scale=1.0, user-scalable=no, width=device-width">
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<link rel="stylesheet" href="../css/ol.css" type="text/css">
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<link rel="stylesheet" href="../resources/bootstrap/css/bootstrap.min.css" type="text/css">
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<link rel="stylesheet" href="../resources/layout.css" type="text/css">
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<link rel="stylesheet" href="../resources/bootstrap/css/bootstrap-responsive.min.css" type="text/css">
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<title>Image Filter Example</title>
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</head>
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<body>
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<div class="navbar navbar-inverse navbar-fixed-top">
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<div class="navbar-inner">
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<div class="container">
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<a class="brand" href="./"><img src="../resources/logo.png"> OpenLayers 3 Examples</a>
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</div>
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</div>
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</div>
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<div class="container-fluid">
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<div class="row-fluid">
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<div class="span12">
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<div id="map" class="map"></div>
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</div>
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</div>
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<div class="row-fluid">
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<div class="span12">
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<h4 id="title">Image filter example</h4>
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<p id="shortdesc">Apply a filter to imagery</p>
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<select id="kernel" name="kernel">
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<option>none</option>
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<option selected>sharpen</option>
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<option value="sharpenless">sharpen less</option>
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<option>blur</option>
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<option>shadow</option>
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<option>emboss</option>
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<option value="edge">edge detect</option>
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</select>
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<div id="docs">
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<p>
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Layer rendering can be manipulated in <code>precompose</code> and <code>postcompose</code> event listeners.
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These listeners get an event with a reference to the Canvas rendering context.
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In this example, the <code>postcompose</code> listener applies a filter to the image data.
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</p>
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<p>See the <a href="image-filter.js" target="_blank">image-filter.js source</a> for details on how this is done.</p>
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</div>
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<div id="tags">filter, image manipulation</div>
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</div>
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</div>
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</div>
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<script src="jquery.min.js" type="text/javascript"></script>
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<script src="../resources/example-behaviour.js" type="text/javascript"></script>
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<script src="loader.js?id=image-filter" type="text/javascript"></script>
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</body>
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</html>
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147
examples/image-filter.js
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examples/image-filter.js
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goog.require('ol.Map');
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goog.require('ol.View2D');
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goog.require('ol.layer.Tile');
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goog.require('ol.proj');
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goog.require('ol.source.BingMaps');
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var key = 'Ak-dzM4wZjSqTlzveKz5u0d4IQ4bRzVI309GxmkgSVr1ewS6iPSrOvOKhA-CJlm3';
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var imagery = new ol.layer.Tile({
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source: new ol.source.BingMaps({key: key, imagerySet: 'Aerial'})
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});
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var map = new ol.Map({
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layers: [imagery],
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renderer: 'canvas',
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target: 'map',
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view: new ol.View2D({
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center: ol.proj.transform([-120, 50], 'EPSG:4326', 'EPSG:3857'),
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zoom: 6
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})
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});
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var kernels = {
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none: [
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0, 0, 0,
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0, 1, 0,
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0, 0, 0
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],
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sharpen: [
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0, -1, 0,
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-1, 5, -1,
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0, -1, 0
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],
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sharpenless: [
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0, -1, 0,
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-1, 10, -1,
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0, -1, 0
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],
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blur: [
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1, 1, 1,
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1, 1, 1,
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1, 1, 1
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],
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shadow: [
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1, 2, 1,
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0, 1, 0,
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-1, -2, -1
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],
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emboss: [
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-2, 1, 0,
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-1, 1, 1,
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0, 1, 2
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],
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edge: [
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0, 1, 0,
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1, -4, 1,
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0, 1, 0
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]
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};
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function normalize(kernel) {
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var len = kernel.length;
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var normal = new Array(len);
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var i, sum = 0;
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for (i = 0; i < len; ++i) {
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sum += kernel[i];
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}
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if (sum <= 0) {
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normal.normalized = false;
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sum = 1;
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} else {
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normal.normalized = true;
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}
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for (i = 0; i < len; ++i) {
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normal[i] = kernel[i] / sum;
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}
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return normal;
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}
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var select = document.getElementById('kernel');
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var selectedKernel = normalize(kernels[select.value]);
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/**
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* Update the kernel and re-render on change.
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*/
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select.onchange = function() {
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selectedKernel = normalize(kernels[select.value]);
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map.render();
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};
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/**
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* Apply a filter on "postcompose" events.
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* @param {ol.render.Event} event Render event.
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*/
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imagery.on('postcompose', function(event) {
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convolve(event.context, selectedKernel);
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});
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/**
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* Apply a convolution kernel to canvas. This works for any size kernel, but
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* performance starts degrading above 3 x 3.
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* @param {CanvasRenderingContext2D} context Canvas 2d context.
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* @param {Array.<number>} kernel Kernel.
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*/
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function convolve(context, kernel) {
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var canvas = context.canvas;
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var width = canvas.width;
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var height = canvas.height;
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var size = Math.sqrt(kernel.length);
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var half = Math.floor(size / 2);
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var inputData = context.getImageData(0, 0, width, height).data;
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var output = context.createImageData(width, height);
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var outputData = output.data;
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for (var pixelY = 0; pixelY < height; ++pixelY) {
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var pixelsAbove = pixelY * width;
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for (var pixelX = 0; pixelX < width; ++pixelX) {
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var r = 0, g = 0, b = 0, a = 0;
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for (var kernelY = 0; kernelY < size; ++kernelY) {
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for (var kernelX = 0; kernelX < size; ++kernelX) {
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var weight = kernel[kernelY * size + kernelX];
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var neighborY = Math.min(
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height - 1, Math.max(0, pixelY + kernelY - half));
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var neighborX = Math.min(
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width - 1, Math.max(0, pixelX + kernelX - half));
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var inputIndex = (neighborY * width + neighborX) * 4;
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r += inputData[inputIndex] * weight;
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g += inputData[inputIndex + 1] * weight;
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b += inputData[inputIndex + 2] * weight;
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a += inputData[inputIndex + 3] * weight;
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}
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}
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var outputIndex = (pixelsAbove + pixelX) * 4;
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outputData[outputIndex] = r;
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outputData[outputIndex + 1] = g;
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outputData[outputIndex + 2] = b;
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outputData[outputIndex + 3] = kernel.normalized ? a : 255;
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}
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}
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context.putImageData(output, 0, 0);
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}
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