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mobile-query-three-vendor-three.js-shaders-ConvolutionShader.js / js



  

author: alteredq / alteredqualia.com/ Convolution shader ported from o3d sample to WebGL / GLSL http://o3d.googlecode.com/svn/trunk/samples/convolution.html

  
  
  THREE.ConvolutionShader = {
  
          defines: {
  
                  "KERNEL_SIZE_FLOAT": "25.0",
                  "KERNEL_SIZE_INT": "25",
  
          },
  
          uniforms: {
  
                  "tDiffuse":        { type: "t", value: null },
                  "uImageIncrement": { type: "v2", value: new THREE.Vector2( 0.001953125, 0.0 ) },
                  "cKernel":         { type: "fv1", value: [] }
  
          },
  
          vertexShader: [
  
                  "uniform vec2 uImageIncrement;",
  
                  "varying vec2 vUv;",
  
                  "void main() {",
  
                          "vUv = uv - ( ( KERNEL_SIZE_FLOAT - 1.0 ) / 2.0 ) * uImageIncrement;",
                          "gl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );",
  
                  "}"
  
          ].join("\n"),
  
          fragmentShader: [
  
                  "uniform float cKernel[ KERNEL_SIZE_INT ];",
  
                  "uniform sampler2D tDiffuse;",
                  "uniform vec2 uImageIncrement;",
  
                  "varying vec2 vUv;",
  
                  "void main() {",
  
                          "vec2 imageCoord = vUv;",
                          "vec4 sum = vec4( 0.0, 0.0, 0.0, 0.0 );",
  
                          "for( int i = 0; i < KERNEL_SIZE_INT; i ++ ) {",
  
                                  "sum += texture2D( tDiffuse, imageCoord ) * cKernel[ i ];",
                                  "imageCoord += uImageIncrement;",
  
                          "}",
  
                          "gl_FragColor = sum;",
  
                  "}"
  
          ].join("\n"),
  
          buildKernel: function ( sigma ) {
  
                  // We lop off the sqrt(2 * pi) * sigma term, since we're going to normalize anyway.
  
                  function gauss( x, sigma ) {
  
                          return Math.exp( - ( x * x ) / ( 2.0 * sigma * sigma ) );
  
                  }
  
                  var i, values, sum, halfWidth, kMaxKernelSize = 25, kernelSize = 2 * Math.ceil( sigma * 3.0 ) + 1;
  
                  if ( kernelSize > kMaxKernelSize ) kernelSize = kMaxKernelSize;
                  halfWidth = ( kernelSize - 1 ) * 0.5;
  
                  values = new Array( kernelSize );
                  sum = 0.0;
                  for ( i = 0; i < kernelSize; ++i ) {
  
                          values[ i ] = gauss( i - halfWidth, sigma );
                          sum += values[ i ];
  
                  }
  
                  // normalize the kernel
  
                  for ( i = 0; i < kernelSize; ++i ) values[ i ] /= sum;
  
                  return values;
  
          }
  
  };
  


(C) Æliens 04/09/2009

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